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hepsim:public [2021/01/19 14:55]
hepsim17 [Publications]
hepsim:public [2022/08/12 12:36]
hepsim17 [Articles]
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 {{indexmenu_n>120}} {{indexmenu_n>120}}
 [[:|<< back to HepSim manual]] [[:|<< back to HepSim manual]]
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 ====== Public results ====== ====== Public results ======
  
-======Publications======+====== Articles ======
  
-Since 2013, there was a number of publications based on the HepSim simulated samples. Here are some of them I'm aware of:+Since 2013, there was a number of articles based on the HepSim simulations. Here are some of them I'm aware of:
  
   * A. V. Kotwal, S. Chekanov, M. Low, Double Higgs Production in the 4τ channel from resonances in longitudinal vector boson scattering at a 100 TeV collider, [[http://arxiv.org/abs/1504.08042|arXiv:1504.08042]]. Phys. Rev. D 91, 114018 (2015)   * A. V. Kotwal, S. Chekanov, M. Low, Double Higgs Production in the 4τ channel from resonances in longitudinal vector boson scattering at a 100 TeV collider, [[http://arxiv.org/abs/1504.08042|arXiv:1504.08042]]. Phys. Rev. D 91, 114018 (2015)
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   * J. Clavijo, P.Glaysher, J.Katzy, Adversarial domain adaptation to reduce sample bias of a high energy physics, DESY 20-073, arXiv:2005.00568    * J. Clavijo, P.Glaysher, J.Katzy, Adversarial domain adaptation to reduce sample bias of a high energy physics, DESY 20-073, arXiv:2005.00568 
   * M.T. Lucchini et. al., "New perspectives on segmented crystal calorimeters for future colliders", (https://arxiv.org/abs/2008.00338), JINST 15 (2020) P11005   * M.T. Lucchini et. al., "New perspectives on segmented crystal calorimeters for future colliders", (https://arxiv.org/abs/2008.00338), JINST 15 (2020) P11005
-  * S. V. Chekanov, G. Gavalian, N. A. Graf, Jas4pp - a Data-Analysis Framework for Physics and Detector Studies, (2020), (https://arxiv.org/abs/2011.05329) (2020) ANL-HEP-164101, SLAC-PUB-17569+  * S. V. Chekanov, G. Gavalian, N. A. Graf, Jas4pp - a Data-Analysis Framework for Physics and Detector Studies, Comp. Physics. Comm. 262 (2021107857, (https://arxiv.org/abs/2011.05329) (2020) ANL-HEP-164101, SLAC-PUB-17569
   * S.Chekanov, Machine Learning Using Rapidity-Mass Matrices for Event Classification Problems in HEP. Universe, 2021, 7(1):19. https://www.mdpi.com/2218-1997/7/1/19   * S.Chekanov, Machine Learning Using Rapidity-Mass Matrices for Event Classification Problems in HEP. Universe, 2021, 7(1):19. https://www.mdpi.com/2218-1997/7/1/19
 +  * J.Pata, et.al. MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks. [[https://inspirehep.net/literature/1842131 |e-Print: 2101.08578]]
 +  * S.V. Chekanov, S. Darmora, W. Islam, C.E.M. Wagner, J. Zhang, Model-independent searches for new physics in multi-body invariant masses, ANL-HEP-166648, Snowmass21 contribution,  https://arxiv.org/abs/2103.10217. Universe 2021, 7(9), 333; https://www.mdpi.com/2218-1997/7/9/333
 +  * Frank E. Taylor, Applications of pT-xR Variables in Describing Inclusive Cross Sections at the LHC. https://arxiv.org/pdf/2105.01010.pdf
 +  * S.V.Chekanov, Searches for new physics in collision events using a statistical technique for anomaly detection, Proceedings of 50th International Symposium on Multiparticle Dynamics (ISMD2021), 12-16 July 2021,  SciPost Phys. Proc. 10, 015 (2022),  https://arxiv.org/abs/2110.06277
 +  * S. Darmora et. al, Signal optimization studies for dijet resonances in events with identified leptons using machine learning, June 2021, ATL-COM-PHYS-2021-391, https://cds.cern.ch/record/2773239/
 +  *  S.V. Chekanov, W. Hopkins, Event-based anomaly detection for new physics searches at the LHC using machine learning, https://arxiv.org/abs/2111.12119 (2021), ANL-HEP-17239 (also contributed paper)
 +  *  S.Chekanov et al, "Precision timing for collider-experiment-based calorimetry", Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021), March 14, 2022, https://arxiv.org/abs/2203.07286, ANL-HEP-173859, MPP-2022-28
 +  *  B. Nachman et al,  Jets and Jet Substructure at Future Colliders, [[https://arxiv.org/abs/2203.07462]] March 2022, Snowmass21 white paper.
 +  * F. Mokhtar et al.,  Explaining machine-learned particle-flow reconstruction, [[https://arxiv.org/abs/2111.12840]] (2022)
 +  * ATLAS Collaboration, ATLAS Collaboration, Search for new phenomena in multi-body invariant masses in events with at least one isolated lepton and two jets using s√=13 TeV proton-proton collision data collected by the ATLAS detector, July 1, 2022, ATLAS-CONF-2022-048 [[https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/CONFNOTES/ATLAS-CONF-2022-048/ | ATLAS-CONF-2022-048 ]]
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 There are also several ATLAS papers and a number of supporting notes that used Monte Carlo files from the HEPSIM repository. There are also several ATLAS papers and a number of supporting notes that used Monte Carlo files from the HEPSIM repository.
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   * S.Chekanov, A.V.Kotwal, J.List,  M.Vos, Requirements from substructure and jet reconstruction, Snowmass21, Snowmass Community Planning Meeting, October 5-8 (2020), Session 131, [[https://indico.fnal.gov/event/44870/contributions/198860/| PDF talk]]   * S.Chekanov, A.V.Kotwal, J.List,  M.Vos, Requirements from substructure and jet reconstruction, Snowmass21, Snowmass Community Planning Meeting, October 5-8 (2020), Session 131, [[https://indico.fnal.gov/event/44870/contributions/198860/| PDF talk]]
   *  Chih-Hsiang Yeh et al. Timing layers. 4th FCC Physics and Experiments Workshop, Nov 11, 2020, CERN [[https://indico.cern.ch/event/932973/contributions/4059399/ | PDF talk]]   *  Chih-Hsiang Yeh et al. Timing layers. 4th FCC Physics and Experiments Workshop, Nov 11, 2020, CERN [[https://indico.cern.ch/event/932973/contributions/4059399/ | PDF talk]]
 +  * S.Chekanov, S.Magill, Towards simulations of HHCAL for future detectors, CalVision workshop, Univ of Maryland, 29-30 July 2021, PDF file
 +  * S.Chekanov, Machine learning and anomaly detection using rapidity-mass matrices PDF file ISMD2021. 50th International Symposium on Multiparticle Production. (July 12-July 16, as a poster)
 +  * Wasikul I.  Model-Independent Searches for New Physics in Multi-Body Invariant Masses, APS April Meeting 2021, https://meetings.aps.org/Meeting/APR21/Session/G19.1
 +  * S.Chekanov et al., Jas4pp. A Data-Analysis Framework for Physics and Detector Studies. APS April Meeting 2021, https://meetings.aps.org/Meeting/APR21/Session/T19.1
 +  * S.Chekanov et. al, Calorimeter performance studies using Monte Carlo simulations for future collider detectors. CPAD Instrumentation Frontier Workshop 2021, 18-22 March 2021, Stony Brook, NY (https://indico.fnal.gov/event/46746/contributions/210055/)
 +  * J.Crosby, "Searches for new physics in collision events using a statistical technique for anomaly detection", APS April Meeting, Apr 8-14, 2022, https://meetings.aps.org/Meeting/APR22/Session/Q09.4
 +  * S.Chekanov, Event-based anomaly detection for new physics searches at the LHC using machine learning, APS April Meeting, Apr 8-14, 2022, https://meetings.aps.org/Meeting/APR22/Session/Q09.1
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