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CERN Document Server 298 records found  1 - 10nextend  jump to record: Search took 0.56 seconds. 
1.
Search for quantum black hole production in lepton+jet final states using proton--proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector / ATLAS Collaboration
A search for quantum black holes in electron+jet and muon+jet invariant mass spectra is performed with 140 $fb^{-1}$ of data collected by the ATLAS detector in proton--proton collisions at $\sqrt{s}$ = 13 TeV at the Large Hadron Collider. The observed invariant mass spectrum of lepton+jet pairs is consistent with Standard Model expectations. [...]
arXiv:2307.14967; CERN-EP-2023-117.- Geneva : CERN, 2024-02-01 - 28 p. - Published in : 10.1103/PhysRevD.109.032010 Fulltext: EXOT-2018-14-002 - PDF; 2307.14967 - PDF; External link: Previous draft version
2.
Measurement of the inclusive $t\bar{t}$ production cross section in the lepton+jets channel in $pp$ collisions at $\sqrt{s}$= 7 TeV with the ATLAS detector using support vector machines / ATLAS Collaboration
A measurement of the top quark pair-production cross section in the lepton+jets decay channel is presented. It is based on 4.6 fb$^{-1}$ of $\sqrt{s} = 7$ TeV $pp$ collision data collected during 2011 by the ATLAS experiment at the CERN Large Hadron Collider. [...]
arXiv:2212.00571; CERN-EP-2022-191.- Geneva : CERN, 2023-08-01 - 34 p. - Published in : Phys. Rev. D 108 (2023) 032014 Fulltext: 2212.00571 - PDF; Publication - PDF; External link: Previous draft version
3.
TF07 Snowmass Report: Theory of Collider Phenomena / Maltoni, F. (Louvain U., CP3 ; INFN, Bologna ; U. Bologna, DIFA) ; Su, S. (Arizona U.) ; Thaler, J. (MIT, Cambridge, CTP ; IAIFI, Cambridge ; Harvard U.) ; Aarrestad, T.K. (CERN) ; Aboubrahim, A. (Munster U., ITP) ; Adhikari, S. (Kansas U. ; Johns Hopkins U.) ; Agapov, I. (DESY) ; Agashe, K. (Maryland U.) ; Agrawal, P. (Oxford U., Theor. Phys.) ; Airen, S. (Maryland U.) et al.
Theoretical research has long played an essential role in interpreting data from high-energy particle colliders and motivating new accelerators to advance the energy and precision frontiers. [...]
arXiv:2210.02591 ; FERMILAB-FN-1203-QIS.
- 22.
Fermilab Library Server - eConf - Fulltext - Fulltext
4.
Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning / Shanahan, Phiala (MIT) ; Terao, Kazuhiro (SLAC) ; Whiteson, Daniel (UC, Irvine) ; Aarts, Gert (Swansea U. ; ECT, Trento ; Fond. Bruno Kessler, Trento) ; Adelmann, Andreas (Northeastern U. ; PSI, Villigen) ; Akchurin, N. (Texas Tech.) ; Alexandru, Andrei (George Washington U. ; Maryland U.) ; Amram, Oz (Johns Hopkins U.) ; Andreassen, Anders (Google Inc.) ; Apresyan, Artur (Fermilab) et al.
The rapidly-developing intersection of machine learning (ML) with high-energy physics (HEP) presents both opportunities and challenges to our community. [...]
arXiv:2209.07559 ; FERMILAB-CONF-22-719-ND-PPD-QIS-SCD.
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Fermilab Library Server - eConf - Fulltext - Fulltext
5.
Measurement of the top-quark mass using a leptonic invariant mass in $pp$ collisions at $\sqrt{s}=13~\textrm{TeV}$ with the ATLAS detector / ATLAS Collaboration
A measurement of the top-quark mass ($m_t$) in the $t\bar{t}\rightarrow~\textrm{lepton}+\textrm{jets}$ channel is presented, with an experimental technique which exploits semileptonic decays of $b$-hadrons produced in the top-quark decay chain. The distribution of the invariant mass $m_{\ell\mu}$ of the lepton, $\ell$ (with $\ell=e,\mu$), from the $W$-boson decay and the muon, $\mu$, originating from the $b$-hadron decay is reconstructed, and a binned-template profile likelihood fit is performed to extract $m_t$. [...]
arXiv:2209.00583; CERN-EP-2020-018.- Geneva : CERN, 2023-06-05 - 54 p. - Published in : JHEP 2306 (2023) 019 Fulltext: 2209.00583 - PDF; document - PDF; External link: Previous draft version
6.
Applications and Techniques for Fast Machine Learning in Science / Deiana, Allison McCarn (Southern Methodist U.) ; Tran, Nhan (Fermilab ; Northwestern U. (main)) ; Agar, Joshua (Lehigh U. (main)) ; Blott, Michaela (Xilinx, Dublin) ; Di Guglielmo, Giuseppe (Columbia U. (main)) ; Duarte, Javier (UC, San Diego) ; Harris, Philip (MIT) ; Hauck, Scott (George Washington U. (main)) ; Liu, Mia (Purdue U.) ; Neubauer, Mark S. (Illinois U., Urbana) et al.
In this community review report, we discuss applications and techniques for fast machine learning (ML) in science -- the concept of integrating power ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. [...]
arXiv:2110.13041; FERMILAB-PUB-21-502-AD-E-SCD.- 2022-04-12 - 56 p. - Published in : Front. Big Data 5 (2022) 787421 Fulltext: 2110.13041 - PDF; fermilab-pub-21-502-ad-e-scd - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server
7.
Two-particle Bose–Einstein correlations in ${ pp }$ collisions at $\mathbf {\sqrt{s} = 13}$ TeV measured with the ATLAS detector at the LHC / ATLAS Collaboration
This paper presents studies of Bose-Einstein correlations (BEC) in proton-proton collisions at a centre-of-mass energy of 13 TeV, using data from the ATLAS detector at the CERN Large Hadron Collider. Data were collected in a special low-luminosity configuration with a minimum-bias trigger and a high-multiplicity track trigger, accumulating integrated luminosities of 151 $\mu$b$^{-1}$ and 8.4 nb$^{-1}$ respectively. [...]
arXiv:2202.02218; CERN-EP-2021-172.- Geneva : CERN, 2022-07-11 - 38 p. - Published in : Eur. Phys. J. C 82 (2022) 608 Fulltext: 2202.02218 - PDF; document - PDF; External link: Previous draft version
8.
Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs / Heintz, Aneesh (Cornell U.) ; Razavimaleki, Vesal (UC, San Diego) ; Duarte, Javier (UC, San Diego) ; DeZoort, Gage (Princeton U.) ; Ojalvo, Isobel (Princeton U.) ; Thais, Savannah (Princeton U.) ; Atkinson, Markus (Illinois U., Urbana) ; Neubauer, Mark (Illinois U., Urbana) ; Gray, Lindsey (Fermilab) ; Jindariani, Sergo (Fermilab) et al.
We develop and study FPGA implementations of algorithms for charged particle tracking based on graph neural networks. [...]
arXiv:2012.01563 ; FERMILAB-CONF-20-622-CMS-SCD.
- 8 p.
Fermilab Library Server - Fulltext - Fulltext
9.
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 / ATLAS Collaboration
Measurements of both the inclusive and differential production cross sections of a top-quark-antiquark pair in association with a $Z$ boson ($t\bar{t}Z$) are presented. The measurements are performed by targeting final states with three or four isolated leptons (electrons or muons) and are based on $\sqrt{s} = 13$ TeV proton-proton collision data with an integrated luminosity of 139 fb$^{-1}$, recorded from 2015 to 2018 with the ATLAS detector at the CERN Large Hadron Collider. [...]
arXiv:2103.12603; CERN-EP-2021-01.- 2021-08-16 - 60 p. - Published in : Eur. Phys. J. C 81 (2021) 737 Fulltext: 2103.12603 - PDF; document - PDF;
10.
Software Training in HEP / Malik, Sudhir (Puerto Rico U., Mayaguez) ; Meehan, Samuel (CERN) ; Lieret, Kilian (LMU Munich (main)) ; Evans, Meirin Oan (Sussex U.) ; Villanueva, Michel H. (Mississippi U.) ; Katz, Daniel S. (Illinois U., Urbana) ; Stewart, Graeme A. (CERN) ; Elmer, Peter (Princeton U.) ; Aziz, Sizar (IJCLab, Orsay) ; Bellis, Matthew (Siena Coll., Loudonville) et al.
Long term sustainability of the high energy physics (HEP) research software ecosystem is essential for the field. With upgrades and new facilities coming online throughout the 2020s this will only become increasingly relevant throughout this decade [...]
arXiv:2103.00659.- 2021-10-08 - 7 p.
- Published in : Comput. Softw. Big Sci.: 5 (2021) , no. 1, pp. 22 Fulltext: document - PDF; 2103.00659 - PDF;
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.22

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