HEPData

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Search for an anomalous excess of charged-current quasi-elastic $\nu_e$ interactions with the MicroBooNE experiment using Deep-Learning-based reconstruction

The MicroBooNE collaboration Abratenko, P. ; An, R. ; Anthony, J. ; et al.

Phys.Rev.D 105 (2022) 112003, 2022.

Inspire Record 1953568 DOI 10.17182/hepdata.114859

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

7 data tables

NuE data and background (+ LEE) constrained prediction

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

NuE data and background (+ LEE) unconstrained prediction

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 constrained fractional covariance matrix

NuE background fractional covariance matrix after the 1mu1p constraint from arXiv:2110.14080

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First Measurement of Energy-dependent Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

The MicroBooNE collaboration Abratenko, P. ; An, R. ; Anthony, J. ; et al.

Phys.Rev.Lett. 128 (2022) 151801, 2022.

Inspire Record 1954078 DOI 10.17182/hepdata.114863

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.

9 data tables

sigmaEnu

$\nu_\mu$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.

dsigmadEmu

$\nu_\mu$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.

dsigmadnu

$\nu_\mu$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.

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Version 3
Search for an anomalous excess of inclusive charged-current $\nu_e$ interactions in the MicroBooNE experiment using Wire-Cell reconstruction

The MicroBooNE collaboration Abratenko, P. ; An, R. ; Anthony, J. ; et al.

Phys.Rev.D 105 (2022) 112005, 2022.

Inspire Record 1953539 DOI 10.17182/hepdata.114862

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.

135 data tables

Constrained $\nu_e$CC FC

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.

Constrained $\nu_e$CC FC

11 channel Covariance Matrix, LEE(x=0.0)

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, LEE(x=0.1)

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, LEE(x=0.2)

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, LEE(x=0.3)

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, LEE(x=0.4)

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, LEE(x=0.5)

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, LEE(x=0.6)

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, LEE(x=0.7)

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, LEE(x=0.8)

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, LEE(x=0.9)

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, LEE(x=1.0)

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, LEE(x=1.1)

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, LEE(x=1.2)

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, LEE(x=1.3)

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, LEE(x=1.4)

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, LEE(x=1.5)

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, LEE(x=1.6)

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, LEE(x=1.7)

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, LEE(x=1.8)

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, LEE(x=1.9)

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, LEE(x=2.0)

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.

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Search for Neutrino-Induced Neutral Current $\Delta$ Radiative Decay in MicroBooNE and a First Test of the MiniBooNE Low Energy Excess Under a Single-Photon Hypothesis

The MicroBooNE collaboration Abratenko, P. ; An, R. ; Anthony, J. ; et al.

Phys.Rev.Lett. 128 (2022) 111801, 2022.

Inspire Record 1937333 DOI 10.17182/hepdata.114860

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

12 data tables

Figure 1(a) Top Panel

Data and MC comparison of the reconstructed $\pi^0$ momentum distribution for the 2$\gamma$1p selected events

Figure 1(a) Bottom Panel

Data/MC ratio as a function of reconstructed $\pi^0$ momentum for the 2$\gamma$1p selection

Figure 1(b) Top Panel

Data and MC comparison of the reconstructed $\pi^0$ momentum distribution for the 2$\gamma$0p selected events

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Updated MiniBooNE Neutrino Oscillation Results with Increased Data and New Background Studies

The MiniBooNE collaboration Aguilar-Arevalo, A.A. ; Brown, B.C. ; Conrad, J.M. ; et al.

Phys.Rev.D 103 (2021) 052002, 2021.

Inspire Record 1804293 DOI 10.17182/hepdata.114365

The MiniBooNE experiment at Fermilab reports a total excess of $638.0 \pm 132.8$ electron-like events ($4.8 \sigma$) from a data sample corresponding to $18.75 \times 10^{20}$ protons-on-target in neutrino mode, which is a 46\% increase in the data sample with respect to previously published results, and $11.27 \times 10^{20}$ protons-on-target in antineutrino mode. The additional statistics allow several studies to address questions on the source of the excess. First, we provide two-dimensional plots in visible energy and cosine of the angle of the outgoing lepton, which can provide valuable input to models for the event excess. Second, we test whether the excess may arise from photons that enter the detector from external events or photons exiting the detector from $\pi^0$ decays in two model independent ways. Beam timing information shows that almost all of the excess is in time with neutrinos that interact in the detector. The radius distribution shows that the excess is distributed throughout the volume, while tighter cuts on the fiducal volume increase the significance of the excess. We conclude that models of the event excess based on entering and exiting photons are disfavored.

15 data tables

$1\sigma$ Limits

The frequentist $1\sigma$ confidence region in $\sin^2(2\theta)$ $\Delta m^2$ for a 2-neutrino muon-to-electron oscillation fit.

$90\%$ Limits

The frequentist $90\%$ confidence region in $\sin^2(2\theta)$ $\Delta m^2$ for a 2-neutrino muon-to-electron oscillation fit.

$99\%$ Limits

The frequentist $99\%$ confidence region in $\sin^2(2\theta)$ $\Delta m^2$ for a 2-neutrino muon-to-electron oscillation fit.

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Measurement of energy flow, cross section and average inelasticity of forward neutrons produced in $\mathrm{\sqrt{s} = 13 TeV}$ proton-proton collisions with the LHCf Arm2 detector

The LHCf collaboration Adriani, O. ; Berti, E. ; Bonechi, L. ; et al.

JHEP 07 (2020) 016, 2020.

Inspire Record 1783943 DOI 10.17182/hepdata.130268

In this paper, we report the measurement of the energy flow, the cross section and the average inelasticity of forward neutrons (+ antineutrons) produced in $\sqrt{s} = 13$ TeV proton-proton collisions. These quantities are obtained from the inclusive differential production cross section, measured using the LHCf Arm2 detector at the CERN Large Hadron Collider. The measurements are performed in six pseudorapidity regions: three of them ($\eta > 10.75$, $8.99 < \eta < 9.21$ and $8.80 < \eta < 8.99$), albeit with smaller acceptance and larger uncertainties, were already published in a previous work, whereas the remaining three ($10.06 < \eta < 10.75$, $9.65 < \eta < 10.06$ and $8.65 < \eta < 8.80$) are presented here for the first time. The analysis was carried out using a data set acquired in June 2015 with a corresponding integrated luminosity of $\mathrm{0.194~nb^{-1}}$. Comparing the experimental measurements with the expectations of several hadronic interaction models used to simulate cosmic ray air showers, none of these generators resulted to have a satisfactory agreement in all the phase space selected for the analysis. The inclusive differential production cross section for $\eta > 10.75$ is not reproduced by any model, whereas the results still indicate a significant but less serious deviation at lower pseudorapidities. Depending on the pseudorapidity region, the generators showing the best overall agreement with data are either SIBYLL 2.3 or EPOS-LHC. Furthermore, apart from the most forward region, the derived energy flow and cross section distributions are best reproduced by EPOS-LHC. Finally, even if none of the models describe the elasticity distribution in a satisfactory way, the extracted average inelasticity is consistent with the QGSJET II-04 value, while most of the other generators give values that lie just outside the experimental uncertainties.

9 data tables

Table 1

Neutron (and antineutron) inclusive differential production cross section in $\eta > 10.75$

Table 2

Neutron (and antineutron) inclusive differential production cross section in $10.06 < \eta < 10.75$

Table 3

Neutron (and antineutron) inclusive differential production cross section in $9.65 < \eta < 10.06$

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rivet Analysis
Measurement of inclusive forward neutron production cross section in proton-proton collisions at $\mathrm{\sqrt{s} = 13~TeV}$ with the LHCf Arm2 detector

The LHCf collaboration Adriani, O. ; Berti, E. ; Bonechi, L. ; et al.

JHEP 11 (2018) 073, 2018.

Inspire Record 1692008 DOI 10.17182/hepdata.87099

In this paper, we report the measurement relative to the production of forward neutrons in proton-proton collisions at $\mathrm{\sqrt{s} = 13~TeV}$ obtained using the LHCf Arm2 detector at the Large Hadron Collider. The results for the inclusive differential production cross section are presented as a function of energy in three different pseudorapidity regions: $\eta > 10.76$, $8.99 < \eta < 9.22$ and $8.81 < \eta < 8.99$. The analysis was performed using a data set acquired in June 2015 that corresponds to an integrated luminosity of $\mathrm{0.194~nb^{-1}}$. The measurements were compared with the predictions of several hadronic interaction models used to simulate air showers generated by Ultra High Energy Cosmic Rays. None of these generators showed good agreement with the data for all pseudorapidity intervals. For $\eta > 10.76$, no model is able to reproduce the observed peak structure at around $\mathrm{5~TeV}$ and all models underestimate the total production cross section: among them, QGSJET II-04 shows the smallest deficit with respect to data for the whole energy range. For $8.99 < \eta < 9.22$ and $8.81 < \eta < 8.99$, the models having the best overall agreement with data are SIBYLL 2.3 and EPOS-LHC, respectively: in particular, in both regions SIBYLL 2.3 is able to reproduce the observed peak structure at around $\mathrm{1.5-2.5~TeV}$.

3 data tables

Table 1

Inclusive neutron (and antineutron) production cross section in $\eta > 10.76$

Table 2

Inclusive neutron (and antineutron) production cross section in $8.99 < \eta < 9.22$

Table 3

Inclusive neutron (and antineutron) production cross section in $8.81 < \eta < 8.99$

Beam-energy and centrality dependence of direct-photon emission from ultra-relativistic heavy-ion collisions

The PHENIX collaboration Adare, A. ; Afanasiev, S. ; Aidala, C. ; et al.

Phys.Rev.Lett. 123 (2019) 022301, 2019.

Inspire Record 1672476 DOI 10.17182/hepdata.110699

The PHENIX collaboration presents first measurements of low-momentum ($0.4<p_T<3$ GeV/$c$) direct-photon yields from Au$+$Au collisions at $\sqrt{s_{_{NN}}}$=39 and 62.4 GeV. For both beam energies the direct-photon yields are substantially enhanced with respect to expectations from prompt processes, similar to the yields observed in Au$+$Au collisions at $\sqrt{s_{_{NN}}}$=200. Analyzing the photon yield as a function of the experimental observable $dN_{\rm ch}/d\eta$ reveals that the low-momentum ($>$1\,GeV/$c$) direct-photon yield $dN_{\gamma}^{\rm dir}/d\eta$ is a smooth function of $dN_{\rm ch}/d\eta$ and can be well described as proportional to $(dN_{\rm ch}/d\eta)^\alpha$ with $\alpha{\sim}$1.25. This new scaling behavior holds for a wide range of beam energies at the Relativistic Heavy Ion Collider and Large Hadron Collider, for centrality selected samples, as well as for different, $A$$+$$A$ collision systems. At a given beam energy the scaling also holds for high $p_T$ ($>5$\,GeV/$c$) but when results from different collision energies are compared, an additional $\sqrt{s_{_{NN}}}$-dependent multiplicative factor is needed to describe the integrated-direct-photon yield.

21 data tables

Figure1pp200

Direct photon spectra(Physical Review C87, 054907 (2013)) normalized by $(dN_{ch}/d\eta)^{1.25}$ for in p+p at $\sqrt{s_{NN}}$= 200 GeV.

Figure1pp624

Direct photon spectra(Physics Letters B94, 106 (1980)) normalized by $(dN_{ch}/d\eta)^{1.25}$ for in p+p at $\sqrt{s_{NN}}$= 62.4 GeV.

Figure1pp63

Direct photon spectra(Nucl. Part. Phys. 23, A1 (1997) and Sov. J. Nucl. Phys. 51, 836 (1990)) normalized by $(dN_{ch}/d\eta)^{1.25}$ for in p+p at $\sqrt{s_{NN}}$= 63 GeV.

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Photoproduction of $\Lambda$ and $\Sigma^{0}$ hyperons off protons with linearly polarized photons at $E_{\gamma} = 1.5-3.0$ GeV

The LEPS collaboration Shiu, S.H. ; Kohri, H. ; Chang, W.C. ; et al.

Phys.Rev.C 97 (2018) 015208, 2018.

Inspire Record 1636280 DOI 10.17182/hepdata.81998

We report the measurement of the $\gamma p \rightarrow K^{+}\Lambda$ and $\gamma p \rightarrow K^{+}\Sigma^{0}$ reactions at SPring-8. The differential cross sections and photon-beam asymmetries are measured at forward $K^{+}$ production angles using linearly polarized tagged-photon beams in the range of $E_{\gamma}=1.5$--3.0 GeV. With increasing photon energy, the cross sections for both $\gamma p \rightarrow K^{+}\Lambda$ and $\gamma p \rightarrow K^{+}\Sigma^{0}$ reactions decrease slowly. Distinct narrow structures in the production cross section have not been found at $E_{\gamma}=1.5$--3.0 GeV. The forward peaking in the angular distributions of cross sections, a characteristic feature of $t$-channel exchange, is observed for the production of $\Lambda$ in the whole observed energy range. A lack of similar feature for $\Sigma^{0}$ production reflects a less dominant role of $t$-channel contribution in this channel. The photon-beam asymmetries remain positive for both reactions, suggesting the dominance of $K^{*}$ exchange in the $t$ channel. These asymmetries increase gradually with the photon energy, and have a maximum value of +0.6 for both reactions. Comparison with theoretical predictions based on the Regge trajectory in the $t$ channel and the contributions of nucleon resonances indicates the major role of $t$-channel contributions as well as non-negligible effects of nucleon resonances in accounting for the reaction mechanism of hyperon photoproduction in this photon energy regime.

46 data tables

Table 1

Differential cross sections for the GAMMA P --> K+ LAMBDA reaction as a function of photon energy Egamma for the kaon c.m. production polar angle 0.6 < cos(theta) < 0.7.

Table 2

Differential cross sections for the GAMMA P --> K+ LAMBDA reaction as a function of photon energy Egamma for the kaon c.m. production polar angle 0.7 < cos(theta) < 0.8.

Table 3

Differential cross sections for the GAMMA P --> K+ LAMBDA reaction as a function of photon energy Egamma for the kaon c.m. production polar angle 0.8 < cos(theta) < 0.9.

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rivet Analysis
Measurement of forward photon production cross-section in proton–proton collisions at $\sqrt{s}$ = 13 TeV with the LHCf detector

The LHCf collaboration Adriani, O. ; Berti, E. ; Bonechi, L. ; et al.

Phys.Lett.B 780 (2018) 233-239, 2018.

Inspire Record 1518782 DOI 10.17182/hepdata.86566

In this paper, we report the production cross-section of forward photons in the pseudorapidity regions of $\eta\,>\,10.94$ and $8.99\,>\,\eta\,>\,8.81$, measured by the LHCf experiment with proton--proton collisions at $\sqrt{s}$ = 13 TeV. The results from the analysis of 0.191 $\mathrm{nb^{-1}}$ of data obtained in June 2015 are compared to the predictions of several hadronic interaction models that are used in air-shower simulations for ultra-high-energy cosmic rays. Although none of the models agree perfectly with the data, EPOS-LHC shows the best agreement with the experimental data among the models.

2 data tables

Table 1

Inclusive photon production cross section in $\eta > 10.94$

Table 2

Inclusive photon production cross section in $8.81<\eta<8.99$

Date

Collaboration

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Phrases

Observables

CM Energies (GeV)

Authors Reset

Search for an anomalous excess of charged-current quasi-elastic $\nu_e$ interactions with the MicroBooNE experiment using Deep-Learning-based reconstruction

First Measurement of Energy-dependent Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

Version 3
Search for an anomalous excess of inclusive charged-current $\nu_e$ interactions in the MicroBooNE experiment using Wire-Cell reconstruction

Search for Neutrino-Induced Neutral Current $\Delta$ Radiative Decay in MicroBooNE and a First Test of the MiniBooNE Low Energy Excess Under a Single-Photon Hypothesis

Updated MiniBooNE Neutrino Oscillation Results with Increased Data and New Background Studies

Measurement of energy flow, cross section and average inelasticity of forward neutrons produced in $\mathrm{\sqrt{s} = 13 TeV}$ proton-proton collisions with the LHCf Arm2 detector

rivet Analysis
Measurement of inclusive forward neutron production cross section in proton-proton collisions at $\mathrm{\sqrt{s} = 13~TeV}$ with the LHCf Arm2 detector

Beam-energy and centrality dependence of direct-photon emission from ultra-relativistic heavy-ion collisions

Photoproduction of $\Lambda$ and $\Sigma^{0}$ hyperons off protons with linearly polarized photons at $E_{\gamma} = 1.5-3.0$ GeV

rivet Analysis
Measurement of forward photon production cross-section in proton–proton collisions at $\sqrt{s}$ = 13 TeV with the LHCf detector

Date

Collaboration

Subject_areas

Phrases

Observables

CM Energies (GeV)

Authors Reset

Version 3 Search for an anomalous excess of inclusive charged-current $\nu_e$ interactions in the MicroBooNE experiment using Wire-Cell reconstruction

Version 3
Search for an anomalous excess of inclusive charged-current $\nu_e$ interactions in the MicroBooNE experiment using Wire-Cell reconstruction