Cosmic Ray Background Removal With Deep Neural Networks in SBND

Frontiers in Artificial Intelligence Frontiers 4 (2021) 649917

Authors:

R Acciarri, C Adams, C Andreopoulos, J Asaadi, M Babicz, C Backhouse, W Badgett, L Bagby, D Barker, V Basque, MCQ Bazetto, M Betancourt, A Bhanderi, A Bhat, C Bonifazi, D Brailsford, AG Brandt, T Brooks, MF Carneiro, Y Chen, H Chen, G Chisnall, JI Crespo-Anadón, E Cristaldo, C Cuesta, IL de Icaza Astiz, A De Roeck, G de Sá Pereira, M Del Tutto, V Di Benedetto, A Ereditato, JJ Evans, AC Ezeribe, RS Fitzpatrick, BT Fleming, W Foreman, D Franco, I Furic, AP Furmanski, S Gao, D Garcia-Gamez, H Frandini, G Ge, I Gil-Botella, S Gollapinni, O Goodwin, P Green, WC Griffith, R Guenette, P Guzowski, T Ham, J Henzerling, A Holin, B Howard, RS Jones, D Kalra, G Karagiorgi, L Kashur, W Ketchum, MJ Kim, VA Kudryavtsev, J Larkin, H Lay, I Lepetic, BR Littlejohn, WC Louis, AA Machado, M Malek, D Mardsen, C Mariani, F Marinho, A Mastbaum, K Mavrokoridis, N McConkey, V Meddage, DP Méndez, T Mettler, K Mistry, A Mogan, J Molina, M Mooney, L Mora, CA Moura, J Mousseau, A Navrer-Agasson, FJ Nicolas-Arnaldos, JA Nowak, O Palamara, V Pandey, J Pater, L Paulucci, VL Pimentel, F Psihas, G Putnam, X Qian, E Raguzin, H Ray, M Reggiani-Guzzo, D Rivera, M Roda, M Ross-Lonergan, G Scanavini, A Scarff, DW Schmitz, A Schukraft, E Segreto, M Soares Nunes, M Soderberg, S Söldner-Rembold, J Spitz, NJC Spooner, M Stancari, GV Stenico, A Szelc, W Tang, J Tena Vidal, D Torretta, M Toups, C Touramanis, M Tripathi, S Tufanli, E Tyley, GA Valdiviesso, E Worcester, M Worcester, G Yarbrough, J Yu, B Zamorano, J Zennamo, A Zglam

An error analysis toolkit for binned counting experiments

EPJ Web of Conferences EDP Sciences 251 (2021)

Authors:

Ben Messerly, Rob Fine, Andrew Olivier, X-G Lu, Kang Yang

Abstract:

We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.

Measurements of the inclusive and differential production cross sections of a top-quark–antiquark pair in association with a Z boson at $$\sqrt{s} = 13$$ TeV with the ATLAS detector

The European Physical Journal C SpringerOpen 81:8 (2021) 737

Authors:

G Aad, B Abbott, DC Abbott, A Abed Abud, K Abeling, DK Abhayasinghe, SH Abidi, OS AbouZeid, NL Abraham, H Abramowicz, H Abreu, Y Abulaiti, BS Acharya, B Achkar, L Adam, C Adam Bourdarios, L Adamczyk, L Adamek, J Adelman, A Adiguzel, S Adorni, T Adye, AA Affolder, Y Afik, C Agapopoulou

Abstract:

Abstract Measurements of both the inclusive and differential production cross sections of a top-quark–antiquark pair in association with a Z boson ( $$t{\bar{t}}Z$$ t t ¯ Z ) are presented. The measurements are performed by targeting final states with three or four isolated leptons (electrons or muons) and are based on $$\sqrt{s} = 13$$ s = 13 TeV proton–proton collision data with an integrated luminosity of 139 $$\hbox {fb}^{-1}$$ fb - 1 , recorded from 2015 to 2018 with the ATLAS detector at the CERN Large Hadron Collider. The inclusive cross section is measured to be $$\sigma _{t{\bar{t}}Z} = 0.99 \pm 0.05$$ σ t t ¯ Z = 0.99 ± 0.05 (stat.) $$\pm \, 0.08$$ ± 0.08 (syst.) pb, in agreement with the most precise theoretical predictions. The differential measurements are presented as a function of a number of kinematic variables which probe the kinematics of the $$t{\bar{t}}Z$$ t t ¯ Z system. Both absolute and normalised differential cross-section measurements are performed at particle and parton levels for specific fiducial volumes and are compared with theoretical predictions at different levels of precision, based on a $$\chi ^{2}/$$ χ 2 / ndf and p value computation. Overall, good agreement is observed between the unfolded data and the predictions.

Measurements of sensor radiation damage in the ATLAS inner detector using leakage currents

Journal of Instrumentation IOP Publishing 16:08 (2021) P08025-P08025

Authors:

G Aad, B Abbott, DC Abbott, A Abed Abud, K Abeling, DK Abhayasinghe, SH Abidi, OS AbouZeid, NL Abraham, H Abramowicz, H Abreu, Y Abulaiti, AC Abusleme Hoffman, BS Acharya, B Achkar, L Adam, C Adam Bourdarios, L Adamczyk, L Adamek, J Adelman, A Adiguzel, S Adorni, T Adye, AA Affolder, Y Afik

Abstract:

Abstract Non-ionizing energy loss causes bulk damage to the silicon sensors of the ATLAS pixel and strip detectors. This damage has important implications for data-taking operations, charged-particle track reconstruction, detector simulations, and physics analysis. This paper presents simulations and measurements of the leakage current in the ATLAS pixel detector and semiconductor tracker as a function of location in the detector and time, using data collected in Run 1 (2010–2012) and Run 2 (2015–2018) of the Large Hadron Collider. The extracted fluence shows a much stronger | z |-dependence in the innermost layers than is seen in simulation. Furthermore, the overall fluence on the second innermost layer is significantly higher than in simulation, with better agreement in layers at higher radii. These measurements are important for validating the simulation models and can be used in part to justify safety factors for future detector designs and interventions.

Measurement of single top-quark production in association with a W boson in the single-lepton channel at $$\sqrt{s} = 8\,\text {TeV}$$ with the ATLAS detector

The European Physical Journal C SpringerOpen 81:8 (2021) 720

Authors:

G Aad, B Abbott, DC Abbott, A Abed Abud, K Abeling, DK Abhayasinghe, SH Abidi, OS AbouZeid, NL Abraham, H Abramowicz, H Abreu, Y Abulaiti, BS Acharya, B Achkar, S Adachi, L Adam, C Adam Bourdarios, L Adamczyk, L Adamek, J Adelman, M Adersberger, A Adiguzel, S Adorni, T Adye, AA Affolder

Abstract:

Abstract The production cross-section of a top quark in association with a W boson is measured using proton–proton collisions at $$\sqrt{s} = 8\,\text {TeV}$$ s=8TeV . The dataset corresponds to an integrated luminosity of $$20.2\,\text {fb}^{-1}$$ 20.2fb-1 , and was collected in 2012 by the ATLAS detector at the Large Hadron Collider at CERN. The analysis is performed in the single-lepton channel. Events are selected by requiring one isolated lepton (electron or muon) and at least three jets. A neural network is trained to separate the tW signal from the dominant $$t{\bar{t}}$$ tt¯ background. The cross-section is extracted from a binned profile maximum-likelihood fit to a two-dimensional discriminant built from the neural-network output and the invariant mass of the hadronically decaying W boson. The measured cross-section is $$\sigma _{tW} = 26 \pm 7\,\text {pb}$$ σtW=26±7pb , in good agreement with the Standard Model expectation.