Observation of single-top-quark production in association with a photon using the ATLAS detector

The ATLAS collaboration Aad, Georges ; Abbott, Braden Keim ; Abbott, D.C. ; et al.
Phys.Rev.Lett. 131 (2023) 181901, 2023.
Inspire Record 2628980 DOI 10.17182/hepdata.134244

This Letter reports the observation of single top quarks produced together with a photon, which directly probes the electroweak coupling of the top quark. The analysis uses 139 fb$^{-1}$ of 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider. Requiring a photon with transverse momentum larger than 20 GeV and within the detector acceptance, the fiducial cross section is measured to be 688 $\pm$ 23 (stat.) $^{+75}_{-71}$ (syst.) fb, to be compared with the standard model prediction of 515 $^{+36}_{-42}$ fb at next-to-leading order in QCD.

26 data tables

This table shows the values for $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b)$ and $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b)+\sigma_{t(\rightarrow l\nu b\gamma)q}$ obtained by a profile-likelihood fit in the fiducial parton-level phase space (defined in Table 1) and particle-level phase space (defined in Table 2), respectively.

Distribution of the reconstructed top-quark mass in the $W\gamma\,$CR before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the NN output in the 0fj$\,$SR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

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First measurement of the forward rapidity gap distribution in pPb collisions at $\sqrt{s_\mathrm{NN}}$ = 8.16 TeV

The CMS collaboration Tumasyan, Armen ; Adam, Wolfgang ; Ambrogi, Federico ; et al.
Phys.Rev.D 108 (2023) 092004, 2023.
Inspire Record 2624308 DOI 10.17182/hepdata.88293

For the first time at LHC energies, the forward rapidity gap spectra from proton-lead collisions for both proton and lead dissociation processes are presented. The analysis is performed over 10.4 units of pseudorapidity at a center-of-mass energy per nucleon pair of $\sqrt{s_\mathrm{NN}}$ = 8.16 TeV, almost 300 times higher than in previous measurements of diffractive production in proton-nucleus collisions. For lead dissociation processes, which correspond to the pomeron-lead event topology, the EPOS-LHC generator predictions are a factor of two below the data, but the model gives a reasonable description of the rapidity gap spectrum shape. For the pomeron-proton topology, the EPOS-LHC, QGSJET II, and HIJING predictions are all at least a factor of five lower than the data. The latter effect might be explained by a significant contribution of ultra-peripheral photoproduction events mimicking the signature of diffractive processes. These data may be of significant help in understanding the high energy limit of quantum chromodynamics and for modeling cosmic ray air showers.

14 data tables

Differential cross section for events with Pomeron-Lead ($\mathrm{I\!P}\mathrm{Pb}$) topology obtained at the reconstruction level for $|\eta| < 3$ region. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

Differential cross section for events with Pomeron-Proton ($\mathrm{I\!P}\mathrm{p} + \gamma \mathrm{p}$) topology obtained at the reconstruction level for $|\eta| < 3$ region. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

Reconstruction level differential cross section spectla, obtained for the central acceptance, $|\eta| < 3$, for events with Pomeron-Lead ($\mathrm{I\!P}\mathrm{Pb}$) topology compared to the to the EPOS-LHC predictions, broken down into the non-diffractive (ND), central diffractive (CD), single diffractive (SD) and double diffractive (DD) components. Forward Rapidity Gap definition: $|\eta| < 2.5$: $p_{T}^{track} < 200$ MeV and $\sum \limits_{bin} E^{PF} < 6$ GeV $|\eta| \in [2.5,3.0]$: $\sum \limits_{bin} E_{neutral}^{PF} < 13.4$ GeV

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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

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

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QCD studies using a cone based jet finding algorithm for e+ e- collisions at LEP

The OPAL collaboration Akers, R. ; Alexander, G. ; Allison, John ; et al.
Z.Phys.C 63 (1994) 197-212, 1994.
Inspire Record 373000 DOI 10.17182/hepdata.48238

We describe a cone-based jet finding algorithm (similar to that used in\(\bar p\)p experiments), which we have applied to hadronic events recorded using the OPAL detector at LEP. Comparisons are made between jets defined with the cone algorithm and jets found by the “JADE” and “Durham” jet finders usually used ine+e− experiments. Measured jet rates, as a function of the cone size and as a function of the minimum jet energy, have been compared with O(αs2) calculations, from which two complementary measurements\(\alpha _s \left( {M_{Z^0 } } \right)\) have been made. The results are\(\alpha _s \left( {M_{Z^0 } } \right)\)=0.116±0.008 and\(\alpha _s \left( {M_{Z^0 } } \right)\)=0.119±0.008 respectively, where the errors include both experimental and theoretical uncertainties. Measurements are presented of the energy flow inside jets defined using the cone algorithm, and compared with equivalent data from\(\bar p\)p interactions, reported by the CDF collaboration. We find that the jets ine+e− are significantly narrower than those observed in\(\bar p\)p. The main contribution to this effect appears to arise from differences between quark- and gluon-induced jets.

16 data tables

Measured 2 jet production rate as a function of EPSILON, the minimum energy of a jet for a fixed cone radius R = 0.7 radians.

Measured 2 jet production rate as a function of R, the jet cone radius, for a fixed value of the minimum jet energy, EPSILON, of 7 GeV.

Measured 3 jet production rate as a function of EPSILON, the minimum energy of a jet for a fixed cone radius R = 0.7 radians.

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