Showing 10 of 296 results
We present a measurement of the $\nu_e$-interaction rate in the MicroBooNE detector that addresses the observed MiniBooNE anomalous low-energy excess (LEE). The approach taken isolates neutrino interactions consistent with the kinematics of charged-current quasi-elastic (CCQE) events. The topology of such signal events has a final state with 1 electron, 1 proton, and 0 mesons ($1e1p$). Multiple novel techniques are employed to identify a $1e1p$ final state, including particle identification that use two methods of deep-learning-based image identification, and event isolation using a boosted decision-tree ensemble trained to recognize two-body scattering kinematics. This analysis selects 25 $\nu_e$-candidate events in the reconstructed neutrino energy range of 200--1200 MeV, while $29.0 \pm 1.9_\text{(sys)} \pm 5.4_\text{(stat)}$ are predicted when using $\nu_\mu$ CCQE interactions as a constraint. We use a simplified model to translate the MiniBooNE LEE observation into a prediction for a $\nu_e$ signal in MicroBooNE. A $\Delta \chi^2$ test statistic, based on the combined Neyman--Pearson $\chi^2$ formalism, is used to define frequentist confidence intervals for the LEE signal strength. Using this technique, in the case of no LEE signal, we expect this analysis to exclude a normalization factor of 0.75 (0.98) times the median MiniBooNE LEE signal strength at 90% ($2\sigma$) confidence level, while the MicroBooNE data yield an exclusion of 0.25 (0.38) times the median MiniBooNE LEE signal strength at 90% ($2\sigma$) confidence
Observed NuE data and background (+ LEE) prediction, including the muon neutrino background prediction from the empirical fit, for arXiv:2110.14080. The prediction incorporates the constraint from the 1mu1p sample
Observed NuE data and background (+ LEE) prediction, including the muon neutrino background prediction from the empirical fit, for arXiv:2110.14080. The prediction does not incorporate the constraint from the 1mu1p sample
NuE background fractional covariance matrix after the 1mu1p constraint from arXiv:2110.14080
NuE background+LEE fractional covariance matrix after the 1mu1p constraint from arXiv:2110.14080
NuE background fractional covariance matrix before the 1mu1p constraint from arXiv:2110.14080
NuE background+LEE fractional covariance matrix before the 1mu1p constraint from arXiv:2110.14080
NuE simulation from arXiv:2110.14080
We report a measurement of the energy-dependent total charged-current cross section $\sigma\left(E_\nu\right)$ for inclusive muon neutrinos scattering on argon, as well as measurements of flux-averaged differential cross sections as a function of muon energy and hadronic energy transfer ($\nu$). Data corresponding to 5.3$\times$10$^{19}$ protons on target of exposure were collected using the MicroBooNE liquid argon time projection chamber located in the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8~GeV. The mapping between the true neutrino energy $E_\nu$ and reconstructed neutrino energy $E^{rec}_\nu$ and between the energy transfer $\nu$ and reconstructed hadronic energy $E^{rec}_{had}$ are validated by comparing the data and Monte Carlo (MC) predictions. In particular, the modeling of the missing hadronic energy and its associated uncertainties are verified by a new method that compares the $E^{rec}_{had}$ distributions between data and an MC prediction after constraining the reconstructed muon kinematic distributions, energy and polar angle, to those of data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well-modeled and underpins first-time measurements of both the total cross section $\sigma\left(E_\nu\right)$ and the differential cross section $d\sigma/d\nu$ on argon.
$\nu_\mu$CC inclusive total cross section per nucleon in each neutrino energy bin with statistical plus systematic uncertainty. The total uncertainty comes from the square root of the covariance matrix diagonal entries.
$\nu_\mu$CC inclusive differential cross section per nucleon in each muon energy bin with statistical plus systematic uncertainty. The total uncertainty comes from the square root of the covariance matrix diagonal entries.
$\nu_\mu$CC inclusive differential cross section per nucleon in each hadronic energy transfer bin with statistical plus systematic uncertainty. The total uncertainty comes from the square root of the covariance matrix diagonal entries.
Covariance matrix of the $\nu_\mu$CC inclusive total cross section per nucleon in neutrino energy bins.
Covariance matrix of the $\nu_\mu$CC inclusive differential cross section per nucleon in muon energy bins.
Covariance matrix of the $\nu_\mu$CC inclusive differential cross section per nucleon in hadronic energy transfer bins.
Additional smearing matrix of the $\nu_\mu$CC inclusive total cross section per nucleon in neutrino energy bins.
Additional smearing matrix of the $\nu_\mu$CC inclusive differential cross section per nucleon in muon energy bins.
Additional smearing matrix of the $\nu_\mu$CC inclusive total cross section per nucleon in neutrino energy bins.
We report a search for an anomalous excess of inclusive charged-current (CC) $\nu_e$ interactions using the Wire-Cell event reconstruction package in the MicroBooNE experiment, which is motivated by the previous observation of a low-energy excess (LEE) of electromagnetic events from the MiniBooNE experiment. With a single liquid argon time projection chamber detector, the measurements of $\nu_{\mu}$ CC interactions as well as $\pi^0$ interactions are used to constrain signal and background predictions of $\nu_e$ CC interactions. A data set collected from February 2016 to July 2018 corresponding to an exposure of 6.369 $\times$ 10$^{20}$ protons on target from the Booster Neutrino Beam at FNAL is analyzed. With $x$ representing an overall normalization factor and referred to as the LEE strength parameter, we select 56 fully contained $\nu_e$ CC candidates while expecting 69.6 $\pm$ 8.0 (stat.) $\pm$ 5.0 (sys.) and 103.8 $\pm$ 9.0 (stat.) $\pm$ 7.4 (sys.) candidates after constraints for the absence (eLEE$_{x=0}$) of the median signal strength derived from the MiniBooNE observation and the presence (eLEE$_{x=1}$) of that signal strength, respectively. Under a nested hypothesis test using both rate and shape information in all available channels, the best-fit $x$ is determined to be 0 (eLEE$_{x=0}$) with a 95.5% confidence level upper limit of $x$ at 0.502. Under a simple-vs-simple hypotheses test, the eLEE$_{x=1}$ hypothesis is rejected at 3.75$\sigma$, while the eLEE$_{x=0}$ hypothesis is shown to be consistent with the observation at 0.45$\sigma$. In the context of the eLEE model, the estimated 68.3% confidence interval of the $\nu_e$ hypothesis to explain the LEE observed in the MiniBooNE experiment is disfavored at a significance level of more than 2.6$\sigma$ (3.0$\sigma$) considering MiniBooNE's full (statistical) uncertainties.
Fully contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions constrained by the $\nu_e$CC PC, $\nu_\mu$CC FC, $\nu_\mu$CC PC, $\nu_\mu$CC $\pi^0$ FC, $\nu_\mu$CC $\pi^0$ PC, and NC $\pi^0$ channels under a LEE(x=0) hypothesis. Note that here we show the sum of the constrained signal and constrained background; due to correlations between signal and background, this is not identical to constraining after summing signal and background, but the difference here is minimal. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Fully contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions constrained by the $\nu_e$CC PC, $\nu_\mu$CC FC, $\nu_\mu$CC PC, $\nu_\mu$CC $\pi^0$ FC, $\nu_\mu$CC $\pi^0$ PC, and NC $\pi^0$ channels under a LEE(x=0) hypothesis. Note that here we show the sum of the constrained signal and constrained background; due to correlations between signal and background, this is not identical to constraining after summing signal and background, but the difference here is minimal. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Fully contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions constrained by the $\nu_e$CC PC, $\nu_\mu$CC FC, $\nu_\mu$CC PC, $\nu_\mu$CC $\pi^0$ FC, $\nu_\mu$CC $\pi^0$ PC, and NC $\pi^0$ channels under a LEE(x=0) hypothesis. Note that here we show the sum of the constrained signal and constrained background; due to correlations between signal and background, this is not identical to constraining after summing signal and background, but the difference here is minimal. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
$\nu_e$ CC FC covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0), the standard prediction with no low energy excess. This has been constrained by the $\nu_e$CC PC, $\nu_\mu$CC FC, $\nu_\mu$CC PC, $\nu_\mu$CC $\pi^0$ FC, $\nu_\mu$CC $\pi^0$ PC, and NC $\pi^0$ channels under a LEE(x=0) hypothesis. The 1-26th bins/rows/columns correspond to the 26 bins of reconstructed neutrino energy in the $\nu_e$CC FC channel.
$\nu_e$ CC FC covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0), the standard prediction with no low energy excess. This has been constrained by the $\nu_e$CC PC, $\nu_\mu$CC FC, $\nu_\mu$CC PC, $\nu_\mu$CC $\pi^0$ FC, $\nu_\mu$CC $\pi^0$ PC, and NC $\pi^0$ channels under a LEE(x=0) hypothesis. The 1-26th bins/rows/columns correspond to the 26 bins of reconstructed neutrino energy in the $\nu_e$CC FC channel.
$\nu_e$ CC FC covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0), the standard prediction with no low energy excess. This has been constrained by the $\nu_e$CC PC, $\nu_\mu$CC FC, $\nu_\mu$CC PC, $\nu_\mu$CC $\pi^0$ FC, $\nu_\mu$CC $\pi^0$ PC, and NC $\pi^0$ channels under a LEE(x=0) hypothesis. The 1-26th bins/rows/columns correspond to the 26 bins of reconstructed neutrino energy in the $\nu_e$CC FC channel.
Fully contained $\nu_e$CC signal efficiency as a function of true neutrino energy. Each bin shows the fraction of Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which are selected in this channel.
Fully contained $\nu_e$CC signal efficiency as a function of true neutrino energy. Each bin shows the fraction of Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which are selected in this channel.
Fully contained $\nu_e$CC signal efficiency as a function of true neutrino energy. Each bin shows the fraction of Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which are selected in this channel.
Partially contained $\nu_e$CC signal efficiency as a function of true neutrino energy. Each bin shows the fraction of Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which are selected in this channel.
Partially contained $\nu_e$CC signal efficiency as a function of true neutrino energy. Each bin shows the fraction of Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which are selected in this channel.
Partially contained $\nu_e$CC signal efficiency as a function of true neutrino energy. Each bin shows the fraction of Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which are selected in this channel.
Fully contained $\nu_e$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of fully contained Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Fully contained $\nu_e$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of selected fully contained Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Fully contained $\nu_e$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of selected fully contained Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Partially contained $\nu_e$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of partially contained Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Partially contained $\nu_e$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of selected partially contained Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Partially contained $\nu_e$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of selected partially contained Monte-Carlo $\nu_e$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Fully contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Fully contained $\nu_\mu$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of selected fully contained Monte-Carlo $\nu_\mu$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Fully contained $\nu_\mu$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of selected fully contained Monte-Carlo $\nu_\mu$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Partially contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Partially contained $\nu_\mu$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of selected partially contained Monte-Carlo $\nu_\mu$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Partially contained $\nu_\mu$CC true neutrino energy vs reconstructed neutrino energy. Each bin shows the relative number of selected partially contained Monte-Carlo $\nu_\mu$ CC events with true neutrino interaction vertex in the fiducial volume (3 cm inside the TPC active volume) which have the corresponding true neutrino energy and reconstructed neutrino energy values. Each axis has 60 bins covering an energy range from 0 to 3 GeV, corresponding to 0.05 GeV per bin.
Fully contained $\nu_\mu$CC data, signal, and background predictions. Events in the $\nu_e$CC or $\pi^0$ selections have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_e$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC events.
Fully contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Fully contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Partially contained $\nu_\mu$CC data, signal, and background predictions. Events in the $\nu_e$CC or $\pi^0$ selections have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_e$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC events.
Partially contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Partially contained $\nu_e$CC data, signal, background, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_\mu$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining intrinsic $\nu_e$CC events. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Fully contained $\nu_\mu$CC$\pi^0$ data, signal, background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes neutral current events, $\nu_e$CC events, $\nu_\mu$CC events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC$\pi^0$ events.
Fully contained $\nu_\mu$CC data, signal, and background predictions. Events in the $\nu_e$CC or $\pi^0$ selections have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_e$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC events.
Fully contained $\nu_\mu$CC data, signal, and background predictions. Events in the $\nu_e$CC or $\pi^0$ selections have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_e$CC events, $\nu_\mu$CC events with greater than or equal to one $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC events.
Partially contained $\nu_\mu$CC$\pi^0$ data, signal, and background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes neutral current events, $\nu_e$CC events, $\nu_\mu$CC events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC$\pi^0$ events.
Partially contained $\nu_\mu$CC data, signal, and background predictions. Events in the $\nu_e$CC or $\pi^0$ selections have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_e$CC events, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC events.
Partially contained $\nu_\mu$CC data, signal, and background predictions. Events in the $\nu_e$CC or $\pi^0$ selections have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The background includes neutral current events, $\nu_e$CC events, $\nu_\mu$CC events with greater than or equal to one $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC events.
NC$\pi^0$ data, signal, and background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes $\nu_e$CC events, $\nu_\mu$CC events, neutral current events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining NC$\pi^0$ events.
Fully contained $\nu_\mu$CC$\pi^0$ data, signal, background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes neutral current events, $\nu_e$CC events, $\nu_\mu$CC events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC$\pi^0$ events.
Fully contained $\nu_\mu$CC$\pi^0$ data, signal, background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes neutral current events, $\nu_e$CC events, $\nu_\mu$CC events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC$\pi^0$ events.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.0), the standard prediction with no low energy excess. No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
Partially contained $\nu_\mu$CC$\pi^0$ data, signal, and background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes neutral current events, $\nu_e$CC events, $\nu_\mu$CC events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC$\pi^0$ events.
Partially contained $\nu_\mu$CC$\pi^0$ data, signal, and background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes neutral current events, $\nu_e$CC events, $\nu_\mu$CC events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining $\nu_\mu$CC$\pi^0$ events.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.1). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
NC$\pi^0$ data, signal, and background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes $\nu_e$CC events, $\nu_\mu$CC events, neutral current events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining NC$\pi^0$ events.
NC$\pi^0$ data, signal, and background predictions. Events in the $\nu_e$CC selection have been removed. Note that the rightmost bin is an overflow bin, containing all events with reconstructed $\pi^0$ kinetic energy greater than 1 GeV. The background includes $\nu_e$CC events, $\nu_\mu$CC events, neutral current events without a $\pi^0$, events with a true neutrino interaction vertex outside the fiducial volume (3 cm inside the TPC active volume), and cosmic ray backgrounds. The signal includes the remaining NC$\pi^0$ events.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.2). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.0), the standard prediction with no low energy excess. No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.0), the standard prediction with no low energy excess. No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.3). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.1). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.1). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.4). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.2). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.2). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.5). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.3). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.3). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.6). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.4). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.4). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.7). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.5). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.5). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.8). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.6). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.6). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.9). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.7). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.7). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.0), the median unfolded MiniBooNE LEE under a $\nu_e$CC hypothesis. No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.8). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.8). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.1). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.9). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.9). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.2). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.0), the median unfolded MiniBooNE LEE under a $\nu_e$CC hypothesis. No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.0), the median unfolded MiniBooNE LEE under a $\nu_e$CC hypothesis. No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.3). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.1). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.1). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.4). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.2). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.2). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.5). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.3). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.3). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.6). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.4). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.4). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.7). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.5). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.5). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.8). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.6). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.6). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.9). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.7). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.7). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=2.0). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.8). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.8). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.9). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.9). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=2.0). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
7 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=2.0). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC PC channel. The 53-78th bins/rows/columns correspond to the $\nu_\mu$CC FC channel. The 79-104th bins/rows/columns correspond to the $\nu_\mu$CC PC channel. The 105-115th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 116-126th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 127-137th bins/rows/columns correspond to the NC$\pi^0$ channel.
Fully contained $\nu_e$CC $0pX\pi$ data, prediction, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Partially contained $\nu_e$CC $0pX\pi$ data, prediction, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Fully contained $\nu_e$CC $NpX\pi$ data, prediction, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Partially contained $\nu_e$CC $NpX\pi$ data, prediction, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Fully contained $\nu_\mu$CC $0pX\pi$ data, prediction, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Partially contained $\nu_\mu$CC $0pX\pi$ data, prediction, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Fully contained $\nu_\mu$CC $NpX\pi$ data, prediction, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
Partially contained $\nu_\mu$CC $NpX\pi$ data, prediction, and LEE(x=1) predictions. Note that the rightmost bin is an overflow bin, containing all events with reconstructed neutrino energy greater than 2.5 GeV. The LEE(x=1) includes the predicted excess from an unfolding of the MiniBooNE LEE under a $\nu_e$CC hypothesis.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.0), the standard prediction with no low energy excess. No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.1). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.2). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.3). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.4). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.5). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.6). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.7). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.8). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=0.9). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.0), the median unfolded MiniBooNE LEE under a $\nu_e$CC hypothesis. No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.1). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.2). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.3). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.4). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.5). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.6). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.7). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.8). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=1.9). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
11 channel covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. For the data statistical uncertainty covariance matrix, (only diagonal elements, not included here), the Neyman, Pearson, or combined Neyman and Pearson (CNP) techniques can be used. This corresponds to LEE(x=2.0). No constraints have been applied at this stage. The 1-26th bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ FC channel. The 27-52nd bins/rows/columns correspond to the $\nu_e$CC $0pX\pi$ PC channel. The 53-78th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ FC channel. The 79-104th bins/rows/columns correspond to the $\nu_e$CC $NpX\pi$ PC channel. The 105-130th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ FC channel. The 131-156th bins/rows/columns correspond to the $\nu_\mu$CC $0pX\pi$ PC channel. The 157-182nd bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ FC channel. The 183-208th bins/rows/columns correspond to the $\nu_\mu$CC $NpX\pi$ PC channel. The 209-219th bins/rows/columns correspond to the CC$\pi^0$ FC channel. The 220-230th bins/rows/columns correspond to the CC$\pi^0$ PC channel. The 231-241st bins/rows/columns correspond to the NC$\pi^0$ channel.
We report results from a search for neutrino-induced neutral current (NC) resonant $\Delta$(1232) baryon production followed by $\Delta$ radiative decay, with a $\langle0.8\rangle$~GeV neutrino beam. Data corresponding to MicroBooNE's first three years of operations (6.80$\times$10$^{20}$ protons on target) are used to select single-photon events with one or zero protons and without charged leptons in the final state ($1\gamma1p$ and $1\gamma0p$, respectively). The background is constrained via an in-situ high-purity measurement of NC $\pi^0$ events, made possible via dedicated $2\gamma1p$ and $2\gamma0p$ selections. A total of 16 and 153 events are observed for the $1\gamma1p$ and $1\gamma0p$ selections, respectively, compared to a constrained background prediction of $20.5 \pm 3.65 \text{(sys.)} $ and $145.1 \pm 13.8 \text{(sys.)} $ events. The data lead to a bound on an anomalous enhancement of the normalization of NC $\Delta$ radiative decay of less than $2.3$ times the predicted nominal rate for this process at the 90% confidence level (CL). The measurement disfavors a candidate photon interpretation of the MiniBooNE low-energy excess as a factor of $3.18$ times the nominal NC $\Delta$ radiative decay rate at the 94.8% CL, in favor of the nominal prediction, and represents a greater than $50$-fold improvement over the world's best limit on single-photon production in NC interactions in the sub-GeV neutrino energy range
Data and MC comparison of the reconstructed $\pi^0$ momentum distribution for the 2$\gamma$1p selected events
Data/MC ratio as a function of reconstructed $\pi^0$ momentum for the 2$\gamma$1p selection
Data and MC comparison of the reconstructed $\pi^0$ momentum distribution for the 2$\gamma$0p selected events
Data/MC ratio as a function of reconstructed $\pi^0$ momentum for the 2$\gamma$0p selection
Energy spectra for the 1$\gamma$1p selected events. The figure shows the unconstrained background prediction and breakdowns as a function of reconstructed shower energy.
Energy spectra for the 1$\gamma$1p selected events. This figure shows the total background prediction with systematic uncertainty both before and after the 2$\gamma$ constraint.
Energy spectra for the 1$\gamma$0p selected events. The figure shows the unconstrained background prediction and breakdowns as a function of reconstructed shower energy.
Energy spectra for the 1$\gamma$0p selected events. This figure shows the total background prediction with systematic uncertainty both before and after the 2$\gamma$ constraint.
The observed event rate for the 1$\gamma$1p event sample, and comparisons to unconstrained (left) and constrained (right) background and LEE model predictions.
The observed event rate for the 1$\gamma$0p event sample, and comparisons to unconstrained (left) and constrained (right) background and LEE model predictions.
The fractional systematic covariance matrix for the final selected 1$\gamma$1p, 1$\gamma$0p, 2$\gamma$1p, and 2$\gamma$0p event samples, in bins of reconstructed shower energy for the 1$\gamma$ distributions, and reconstructed $\pi^{0}$ momentum for the 2$\gamma$ distributions. The bin boundaries are defined in Sec. II in supplementary material. This covariance matrix is evaluated at central value prediction and all variances have been rounded to three significant digits.
The fractional systematic covariance matrix for the final selected 1$\gamma$1p, 1$\gamma$0p, 2$\gamma$1p, and 2$\gamma$0p event samples, in bins of reconstructed shower energy for the 1$\gamma$1p signal, 1$\gamma$1p background, 1$\gamma$0p signal and 1$\gamma$0p background distributions, and reconstructed $\pi^{0}$ momentum for the 2$\gamma$ distributions. The bin boundaries are defined in Sec. II in supplementary material. This covariance matrix is evaluated at central value prediction and variances have been rounded to three significant digits.
Searches for scalar leptoquarks pair-produced in proton-proton collisions at $\sqrt{s}=13$ TeV at the Large Hadron Collider are performed by the ATLAS experiment. A data set corresponding to an integrated luminosity of 36.1 fb$^{-1}$ is used. Final states containing two electrons or two muons and two or more jets are studied, as are states with one electron or muon, missing transverse momentum and two or more jets. No statistically significant excess above the Standard Model expectation is observed. The observed and expected lower limits on the leptoquark mass at 95% confidence level extend up to 1.29 TeV and 1.23 TeV for first- and second-generation leptoquarks, respectively, as postulated in the minimal Buchm\"uller-R\"uckl-Wyler model, assuming a branching ratio into a charged lepton and a quark of 50%. In addition, measurements of particle-level fiducial and differential cross sections are presented for the $Z\rightarrow ee$, $Z\rightarrow\mu\mu$ and $t\bar{t}$ processes in several regions related to the search control regions. Predictions from a range of generators are compared with the measurements, and good agreement is seen for many of the observables. However, the predictions for the $Z\rightarrow\ell\ell$ measurements in observables sensitive to jet energies disagree with the data.
Inclusive cross-section and uncertainty from each source, for the dominant process in the each measurement region.
Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of leading $p_{T}^j$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of subleading $p_{T}^j$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_0,l)$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $min\Delta\phi(j_1,l)$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\eta_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $\Delta\phi_{ll}$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $m_{jj}$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $p_{T}^{ee}$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $p_{T}^{\mu\mu}$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $p_{T}^{e\mu}$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $p_{T}^{ee}$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $p_{T}^{\mu\mu}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $p_{T}^{e\mu}$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $H_{T}$ for the dominant process in the extreme $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $ee jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the $e\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $eejj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $\mu\mu jj$ measurement region.
Differential cross-section and uncertainty from each source, as a function of $S_{T}$ for the dominant process in the extreme $e\mu jj$ measurement region.
Expected and observed 95% CL lower limits on first- and second-generation leptoquark masses for different values of $\beta$.
Event yields in the dimuon channel control regions with total uncertainties. The observed number of events is given in the first row. The background event numbers as obtained from the fit are shown together with the total uncertainties. The second row shows the total background expectation, the further rows show the breakdown into different background components.
Event yields in the dielectron channel control regions with total uncertainties. The observed number of events is given in the first row. The background event numbers as obtained from the fit are shown together with the total uncertainties. The second row shows the total background expectation, the further rows show the breakdown into different background components.
Distribution of $m_{LQ}^{min}$ in the training region for the BDT for the $ee jj$ and $\mu\mu jj$ channels. Data are shown together with predicted total background expectation.
Distribution of $m_{LQ}^{T}$ in the training region for the BDT for the $e\nu jj$ and $\mu\nu jj$ channels. Data are shown together with predicted total background expectation.
A search for heavy right-handed Majorana or Dirac neutrinos $N_R$ and heavy right-handed gauge bosons $W_R$ is performed in events with a pair of energetic electrons or muons, with the same or opposite electric charge, and two energetic jets. The events are selected from $pp$ collision data with an integrated luminosity of 36.1 fb$^{-1}$ collected by the ATLAS detector at $\sqrt{s}$ = 13 TeV. No significant deviations from the Standard Model are observed. The results are interpreted within the theoretical framework of a left-right symmetric model and lower limits are set on masses in the heavy right-handed $W$ boson and neutrino mass plane. The excluded region extends to $m_{W_R}=4.7$ TeV for both Majorana and Dirac $N_R$ neutrinos.
Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $ee$ channel.
Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $ee$ channel.
Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Majorana $N_R$ neutrino $ee$ channel.
Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.
Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.
Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Majorana $N_R$ neutrino $\mu\mu$ channel.
Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.
Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.
Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Dirac $N_R$ neutrino $ee$ channel.
Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.
Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.
Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Dirac $N_R$ neutrino $\mu\mu$ channel.
Observed 95% CL upper limit on cross-section times branching ratio to the $ee$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $ee$ channel.
Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.
Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.
Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.
Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the SS $e^{\pm}e^{\pm}$ channel.
Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the SS $\mu^{\pm}\mu^{\pm}$ channel.
Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the OS $e^{\pm}e^{\mp}$ channel.
Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the OS $\mu^{\pm}\mu^{\mp}$ channel.
Jets created in association with a photon can be used as a calibrated probe to study energy loss in the medium created in nuclear collisions. Measurements of the transverse momentum balance between isolated photons and inclusive jets are presented using integrated luminosities of 0.49 nb$^{-1}$ of Pb+Pb collision data at $\sqrt{s_\mathrm{NN}}=5.02$ TeV and 25 pb$^{-1}$ of $pp$ collision data at $\sqrt{s}=5.02$ TeV recorded with the ATLAS detector at the LHC. Photons with transverse momentum $63.1 < p_\mathrm{T}^{\gamma} < 200$ GeV and $\left|\eta^{\gamma}\right| < 2.37$ are paired inclusively with all jets in the event that have $p_\mathrm{T}^\mathrm{jet} > 31.6$ GeV and pseudorapidity $\left|\eta^\mathrm{jet}\right| < 2.8$. The transverse momentum balance given by the jet-to-photon $p_\mathrm{T}$ ratio, $x_\mathrm{J\gamma}$, is measured for pairs with azimuthal opening angle $\Delta\phi > 7\pi/8$. Distributions of the per-photon jet yield as a function of $x_\mathrm{J\gamma}$, $(1/N_\gamma)(\mathrm{d}N/\mathrm{d}x_\mathrm{J\gamma})$, are corrected for detector effects via a two-dimensional unfolding procedure and reported at the particle level. In $pp$ collisions, the distributions are well described by Monte Carlo event generators. In Pb+Pb collisions, the $x_\mathrm{J\gamma}$ distribution is modified from that observed in $pp$ collisions with increasing centrality, consistent with the picture of parton energy loss in the hot nuclear medium. The data are compared with a suite of energy-loss models and calculations.
Photon-jet pT balance distributions (1/Ng)(dN/dxJg) in pp events (blue, reproduced on all panels) and Pb+Pb events (red) with each panel denoting a different centrality selection. These panels show results with pTg = 63.1-79.6 GeV. Total systematic uncertainties are shown as boxes, while statistical uncertainties are shown with vertical bars.
Photon-jet pT balance distributions (1/Ng)(dN/dxJg) in pp events (blue, reproduced on all panels) and Pb+Pb events (red) with each panel denoting a different centrality selection. These panels show results with pTg = 79.6-100 GeV. Total systematic uncertainties are shown as boxes, while statistical uncertainties are shown with vertical bars.
Photon-jet pT balance distributions (1/Ng)(dN/dxJg) in pp events (blue, reproduced on all panels) and Pb+Pb events (red) with each panel denoting a different centrality selection. These panels show results with pTg = 100-158 GeV. Total systematic uncertainties are shown as boxes, while statistical uncertainties are shown with vertical bars.
Photon-jet pT balance distributions (1/Ng)(dN/dxJg) in pp events (blue, reproduced on all panels) and Pb+Pb events (red) with each panel denoting a different centrality selection. These panels show results with pTg = 158-200 GeV. Total systematic uncertainties are shown as boxes, while statistical uncertainties are shown with vertical bars.
Selected comparisons of the nominal results in pp (blue) and 0-10% Pb+Pb (red) collisions with the central values obtained using a different photon-jet signal definition. Comparison of the nominal results (with DeltaPhi > 7pi/8) with those obtained using DeltaPhi > 3pi/4 for the pTg = 63.1-79.6 GeV range. Boxes indicate total systematic uncertainties, while vertical bars indicate statistical uncertainties.
Selected comparisons of the nominal results in pp (blue) and 0-10% Pb+Pb (red) collisions with the central values obtained using a different photon-jet signal definition. Comparison of the nominal results (inclusive jet selection) with those obtained using a photon-plus-leading-jet selection for the pTg = 100-158 GeV range. Boxes indicate total systematic uncertainties, while vertical bars indicate statistical uncertainties.
Results of a search for the pair production of photon-jets$-$collimated groupings of photons$-$in the ATLAS detector at the Large Hadron Collider are reported. Highly collimated photon-jets can arise from the decay of new, highly boosted particles that can decay to multiple photons collimated enough to be identified in the electromagnetic calorimeter as a single, photonlike energy cluster. Data from proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 36.7 fb$^{-1}$, were collected in 2015 and 2016. Candidate photon-jet pair production events are selected from those containing two reconstructed photons using a set of identification criteria much less stringent than that typically used for the selection of photons, with additional criteria applied to provide improved sensitivity to photon-jets. Narrow excesses in the reconstructed diphoton mass spectra are searched for. The observed mass spectra are consistent with the Standard Model background expectation. The results are interpreted in the context of a model containing a new, high-mass scalar particle with narrow width, $X$, that decays into pairs of photon-jets via new, light particles, $a$. Upper limits are placed on the cross section times the product of branching ratios $\sigma \times \mathcal{B}(X \rightarrow aa) \times \mathcal {B}(a \rightarrow \gamma \gamma)^{2}$ for 200 GeV $< m_{X} <$ 2 TeV and for ranges of $ m_a $ from a lower mass of 100 MeV up to between 2 and 10 GeV, depending upon $ m_X $. Upper limits are also placed on $\sigma \times \mathcal{B}(X \rightarrow aa) \times \mathcal {B}(a \rightarrow 3\pi^{0})^{2}$ for the same range of $ m_X $ and for ranges of $ m_a $ from a lower mass of 500 MeV up to between 2 and 10 GeV.
Distribution of the reconstructed diphoton mass for data events passing the analysis selection, in the low-$\Delta E$ category. There are no data events above 2700 GeV.
Distribution of the reconstructed diphoton mass for data events passing the analysis selection, in the high-$\Delta E$ category. There are no data events above 2700 GeV.
The observed upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 4\gamma$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow\gamma\gamma)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$.
The expected upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 4\gamma$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow\gamma\gamma)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$. Additionally, the expected limits are not provided for a small number of points, indicated with a hyphen, because of a technical failure with the computation.
The observed upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 6\pi^0$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow 3\pi^0)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$.
The expected upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 6\pi^0$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow 3\pi^0)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$. Additionally, the expected limits are not provided for a small number of points, indicated with a hyphen, because of a technical failure with the computation.
Observed 95% CL upper limits on the visible cross section as a function of $m_X$ and the fraction of events in the low-$\Delta E$ category.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.1 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.5 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.7 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 1 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 2 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 5 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 10 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.5 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.7 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 1 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 2 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 5 GeV.
Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 10 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.1 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.5 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.7 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 1 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 2 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 5 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 10 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.5 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.7 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 1 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 2 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 5 GeV.
Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 10 GeV.
Selection efficiency for photons originating from the BSM process $X\rightarrow\gamma\gamma$, where the $X$ particle is a high-mass narrow-width scalar particle originating from the gluon--gluon fusion process.
Fraction of photons with a value of shower shape variable $\Delta E$ lower than the threshold, for photons originating from the BSM process $X\rightarrow\gamma\gamma$, where the $X$ particle is a high-mass narrow-width scalar particle originating from the gluon--gluon fusion process.
A search for supersymmetry in events with large missing transverse momentum, jets, and at least one hadronically decaying $\tau$-lepton is presented. Two exclusive final states with either exactly one or at least two $\tau$-leptons are considered. The analysis is based on proton-proton collisions at $\sqrt{s}$ = 13 TeV corresponding to an integrated luminosity of 36.1 fb$^{-1}$ delivered by the Large Hadron Collider and recorded by the ATLAS detector in 2015 and 2016. No significant excess is observed over the Standard Model expectation. At 95% confidence level, model-independent upper limits on the cross section are set and exclusion limits are provided for two signal scenarios: a simplified model of gluino pair production with $\tau$-rich cascade decays, and a model with gauge-mediated supersymmetry breaking (GMSB). In the simplified model, gluino masses up to 2000 GeV are excluded for low values of the mass of the lightest supersymmetric particle (LSP), while LSP masses up to 1000 GeV are excluded for gluino masses around 1400 GeV. In the GMSB model, values of the supersymmetry-breaking scale are excluded below 110 TeV for all values of $\tan\beta$ in the range $2 \leq \tan\beta \leq 60$, and below 120 TeV for $\tan\beta>30$.
1$\tau$ Compressed SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ MediumMass SR eff.
1$\tau$ MediumMass SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ multibin SR eff.
2$\tau$ multibin SR eff.
2$\tau$ GMSB SR eff.
2$\tau$ GMSB SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ MediumMass SR eff.
1$\tau$ MediumMass SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ multibin SR eff.
2$\tau$ multibin SR eff.
2$\tau$ GMSB SR eff.
2$\tau$ GMSB SR eff.
1$\tau$ Compressed SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ MediumMass SR acceptance.
1$\tau$ MediumMass SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ GMSB SR acceptance.
2$\tau$ GMSB SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ MediumMass SR acceptance.
1$\tau$ MediumMass SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ GMSB SR acceptance.
2$\tau$ GMSB SR acceptance.
Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.
Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.
Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.
Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.
Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.
Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.
Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.
Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.
$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
Measurements of the azimuthal anisotropy in lead-lead collisions at $\sqrt{s_\mathrm{NN}} = 5.02$ TeV are presented using a data sample corresponding to 0.49 $\mathrm{nb}^{-1}$ integrated luminosity collected by the ATLAS experiment at the LHC in 2015. The recorded minimum-bias sample is enhanced by triggers for "ultra-central" collisions, providing an opportunity to perform detailed study of flow harmonics in the regime where the initial state is dominated by fluctuations. The anisotropy of the charged-particle azimuthal angle distributions is characterized by the Fourier coefficients, $v_{2}-v_{7}$, which are measured using the two-particle correlation, scalar-product and event-plane methods. The goal of the paper is to provide measurements of the differential as well as integrated flow harmonics $v_{n}$ over wide ranges of the transverse momentum, 0.5 $
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-0.1%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-1%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-5%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 5-10%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 10-20%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 20-30%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 30-40%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 40-50%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 50-60%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 60-70%
The V2 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 70-80%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-0.1%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-1%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-5%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 5-10%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 10-20%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 20-30%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 30-40%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 40-50%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 50-60%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 60-70%
The V3 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 70-80%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-0.1%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-1%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-5%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 5-10%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 10-20%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 20-30%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 30-40%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 40-50%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 50-60%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 60-70%
The V4 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 70-80%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-0.1%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-1%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-5%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 5-10%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 10-20%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 20-30%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 30-40%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 40-50%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 50-60%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 60-70%
The V5 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 70-80%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-5%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 5-10%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 10-20%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 20-30%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 30-40%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 40-50%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 50-60%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 60-70%
The V6 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 70-80%
The V7 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 0-5%
The V7 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 5-10%
The V7 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 10-20%
The V7 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 20-30%
The V7 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 30-40%
The V7 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 40-50%
The V7 harmonic measured with the scalar product method as a funtion of transverse momentum in centrality bin 50-60%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 0-5%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 5-10%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 10-20%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 20-30%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 30-40%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 40-50%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 50-60%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 60-70%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 70-80%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 0-5%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 5-10%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 10-20%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 20-30%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 30-40%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 40-50%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 50-60%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 60-70%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 70-80%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 0-5%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 5-10%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 10-20%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 20-30%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 30-40%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 40-50%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 50-60%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 60-70%
The V4 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 70-80%
The V5 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 0-5%
The V5 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 5-10%
The V5 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 10-20%
The V5 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 20-30%
The V5 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 30-40%
The V5 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 40-50%
The V5 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 50-60%
The V5 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 60-70%
The V6 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 0-5%
The V6 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 5-10%
The V6 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 10-20%
The V6 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 20-30%
The V6 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 30-40%
The V6 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 40-50%
The V6 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 50-60%
The V6 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 60-70%
The ratio of V2{SP} over V2{EP} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V2{SP} over V2{EP} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V2{SP} over V2{EP} as a funtion of transverse momentum in centrality bin 40-50%
The ratio of V3{SP} over V3{EP} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V3{SP} over V3{EP} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V3{SP} over V3{EP} as a funtion of transverse momentum in centrality bin 40-50%
The ratio of V4{SP} over V4{EP} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V4{SP} over V4{EP} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V4{SP} over V4{EP} as a funtion of transverse momentum in centrality bin 40-50%
The ratio of V5{SP} over V5{EP} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V5{SP} over V5{EP} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V5{SP} over V5{EP} as a funtion of transverse momentum in centrality bin 40-50%
The ratio of V6{SP} over V6{EP} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V6{SP} over V6{EP} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V6{SP} over V6{EP} as a funtion of transverse momentum in centrality bin 40-50%
The ratio of V2{SP} over V2{EP} as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The ratio of V3{SP} over V3{EP} as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The ratio of V4{SP} over V4{EP} as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The ratio of V5{SP} over V5{EP} as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The ratio of V6{SP} over V6{EP} as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The ratio of V2{SP} over V2{2PC} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V2{SP} over V2{2PC} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V2{SP} over V2{2PC} as a funtion of transverse momentum in centrality bin 40-50%
The ratio of V3{SP} over V3{2PC} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V3{SP} over V3{2PC} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V3{SP} over V3{2PC} as a funtion of transverse momentum in centrality bin 40-50%
The ratio of V4{SP} over V4{2PC} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V4{SP} over V4{2PC} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V4{SP} over V4{2PC} as a funtion of transverse momentum in centrality bin 40-50%
The ratio of V5{SP} over V5{2PC} as a funtion of transverse momentum in centrality bin 0-5%
The ratio of V5{SP} over V5{2PC} as a funtion of transverse momentum in centrality bin 20-30%
The ratio of V5{SP} over V5{2PC} as a funtion of transverse momentum in centrality bin 40-50%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%. PT binning matched to RUN1.
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%. PT binning matched to RUN1.
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%. PT binning matched to RUN1.
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%. PT binning matched to RUN1.
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%. PT binning matched to RUN1.
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%. PT binning matched to RUN1.
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%. PT binning matched to RUN1.
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%. PT binning matched to RUN1.
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%. PT binning matched to RUN1.
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%. PT binning matched to RUN1.
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%. PT binning matched to RUN1.
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%. PT binning matched to RUN1.
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%. PT binning matched to RUN1.
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%. PT binning matched to RUN1.
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%. PT binning matched to RUN1.
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-0.1%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-0.1%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-0.1%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-0.1%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V6 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V6 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V6 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V6 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V7 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V7 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V7 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-0.1%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-0.1%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-0.1%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-0.1%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V5 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V6 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V6 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V6 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V6 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V7 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V7 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V7 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-0.1%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-5%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 10-20%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 30-40%
The V2 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 60-70%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-0.1%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-5%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 10-20%
The V3 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 30-40%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-0.1%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-5%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 10-20%
The V4 harmonic measured with the scalar product method as a funtion of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 30-40%
The V2 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V2 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V2 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V2 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V2 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V2 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V2 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V3 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V3 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V3 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V3 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V3 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V3 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V3 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V4 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V4 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V4 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V4 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V4 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V4 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V4 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V5 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V5 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V5 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V5 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V5 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V5 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V5 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V6 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V6 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V6 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V6 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V6 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V6 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V6 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V7 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V7 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V7 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V7 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V7 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V7 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V7 harmonic measured with the scalar product method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 0-5%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 10-15%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 20-25%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 30-35%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 40-45%
The V2 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 50-55%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 0-5%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 10-15%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 20-25%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 30-35%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 40-45%
The V3 harmonic measured with the two particle correlation method as a funtion of transverse momentum in centrality bin 50-55%
The scaled-V2(PT) measured with the two particle correlation method in centrality bin 0-5%
The scaled-V2(PT) measured with the two particle correlation method in centrality bin 10-15%
The scaled-V2(PT) measured with the two particle correlation method in centrality bin 20-25%
The scaled-V2(PT) measured with the two particle correlation method in centrality bin 30-35%
The scaled-V2(PT) measured with the two particle correlation method in centrality bin 40-45%
The scaled-V2(PT) measured with the two particle correlation method in centrality bin 50-55%
The scaled-V3(PT) measured with the two particle correlation method in centrality bin 0-5%
The scaled-V3(PT) measured with the two particle correlation method in centrality bin 10-15%
The scaled-V3(PT) measured with the two particle correlation method in centrality bin 20-25%
The scaled-V3(PT) measured with the two particle correlation method in centrality bin 30-35%
The scaled-V3(PT) measured with the two particle correlation method in centrality bin 40-45%
The scaled-V3(PT) measured with the two particle correlation method in centrality bin 50-55%
The PT scale factor for V2(PT) as a funtion of collision centrality
The PT scale factor for V3(PT) as a funtion of collision centrality
The V2 scale factor as a funtion of collision centrality
The V3 scale factor as a funtion of collision centrality
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-0.1%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-1%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 5-10%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 10-20%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 30-40%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 50-60%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 60-70%
The V2 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 70-80%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-0.1%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-1%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 5-10%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 10-20%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 30-40%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 50-60%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 60-70%
The V3 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 70-80%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-0.1%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-1%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 5-10%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 10-20%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 30-40%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 50-60%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 60-70%
The V4 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 70-80%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-0.1%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-1%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 5-10%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 10-20%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 30-40%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 50-60%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 60-70%
The V5 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 70-80%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 5-10%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 10-20%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 30-40%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 50-60%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 60-70%
The V6 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 70-80%
The V7 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 0-5%
The V7 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 5-10%
The V7 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 10-20%
The V7 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 20-30%
The V7 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 30-40%
The V7 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 40-50%
The V7 harmonic measured with the event plane method as a funtion of transverse momentum in centrality bin 50-60%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-0.1%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-0.1%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-0.1%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-0.1%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V6 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V6 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V6 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V6 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 60-70%
The V7 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 0-5%
The V7 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 10-20%
The V7 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 0.8 < PT < 1 GeV in centrality bin 30-40%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-0.1%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-0.1%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-0.1%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-0.1%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V5 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V6 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V6 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V6 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V6 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 60-70%
The V7 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 0-5%
The V7 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 10-20%
The V7 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 2 < PT < 3 GeV in centrality bin 30-40%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-0.1%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-5%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 10-20%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 30-40%
The V2 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 60-70%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-0.1%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-5%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 10-20%
The V3 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 30-40%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-0.1%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 0-5%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 10-20%
The V4 harmonic measured with the event plane method as a function of pseudorapidity for transverse momentum range 7 < PT < 60 GeV in centrality bin 30-40%
The V2 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V2 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V2 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V2 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V2 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V2 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V2 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V3 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V3 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V3 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V3 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V3 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V3 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V3 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V4 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V4 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V4 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V4 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V4 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V4 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V4 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V5 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V5 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V5 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V5 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V5 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V5 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V5 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V6 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V6 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V6 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V6 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V6 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V6 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V6 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
The V7 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 0.8 GeV
The V7 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.8 < PT < 1 GeV
The V7 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 1 < PT < 2 GeV
The V7 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 2 < PT < 4 GeV
The V7 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 4 < PT < 8 GeV
The V7 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 8 < PT < 60 GeV
The V7 harmonic measured with the event plane method as a funtion of MEAN(Npart) integrated over 0.5 < PT < 60 GeV
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