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hepsim:public [2022/03/15 15:07] hepsim17 |
hepsim:public [2024/05/14 20:04] hepsim17 [HepSim in public talks] |
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* Shin-Shan Yu, etc. Study Of Boosted W-Jets And Higgs-Jets With the SiFCC Detector. Proceedings for the 38th International Conference on High Energy Physics, 3-10 August 2016, Chicago, USA (6 pages, 8 figures), [[https:// | * Shin-Shan Yu, etc. Study Of Boosted W-Jets And Higgs-Jets With the SiFCC Detector. Proceedings for the 38th International Conference on High Energy Physics, 3-10 August 2016, Chicago, USA (6 pages, 8 figures), [[https:// | ||
* Sourav Sen et al. Detectors for Superboosted tau-leptons at Future Circular Colliders. [[http:// | * Sourav Sen et al. Detectors for Superboosted tau-leptons at Future Circular Colliders. [[http:// | ||
+ | * Lee, Sunghee et al, A Data-driven Approach for Computational Simulation: Trend, Requirement and Technology. Journal of Internet Computing and Services, | ||
* M. Beydler et al., Initial performance studies of a general-purpose detector for multi-TeV physics at a 100 TeV pp collider. Dec 2016. [[https:// | * M. Beydler et al., Initial performance studies of a general-purpose detector for multi-TeV physics at a 100 TeV pp collider. Dec 2016. [[https:// | ||
* Effect of PYTHIA8 tunes on event shapes and top-quark reconstruction in e+e− annihilation at CLIC, S.Chekanov, M.Demarteau, | * Effect of PYTHIA8 tunes on event shapes and top-quark reconstruction in e+e− annihilation at CLIC, S.Chekanov, M.Demarteau, | ||
+ | * FCC-hh: The Hadron Collider, Future Circular Collider Conceptual Design Report Volume 3, Eur. Phys. J. Special Topics 228, 755–1107 (2019) | ||
* Precision searches in dijets at the HL-LHC and HE-LHC, S. V. Chekanov, J. T. Childers, D. Frizzell, J. Proudfoot, R. Wang, ANL-HEP-139751, | * Precision searches in dijets at the HL-LHC and HE-LHC, S. V. Chekanov, J. T. Childers, D. Frizzell, J. Proudfoot, R. Wang, ANL-HEP-139751, | ||
* S.V. Chekanov, Imaging particle collision data for event classification using machine learning, May (2018), | * S.V. Chekanov, Imaging particle collision data for event classification using machine learning, May (2018), | ||
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* 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, | * 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, | ||
* Frank E. Taylor, Applications of pT-xR Variables in Describing Inclusive Cross Sections at the LHC. https:// | * Frank E. Taylor, Applications of pT-xR Variables in Describing Inclusive Cross Sections at the LHC. https:// | ||
- | * S.V.Chekanov, | + | * S.V.Chekanov, |
* 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, | * 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, | ||
- | * S.V. Chekanov, W. Hopkins, Event-based anomaly detection for new physics searches at the LHC using machine learning, https:// | + | * S.V. Chekanov, W. Hopkins, Event-based anomaly detection for new physics searches at the LHC using machine learning, https:// |
* S.Chekanov et al, " | * S.Chekanov et al, " | ||
- | + | * B. Nachman et al, Jets and Jet Substructure at Future Colliders, [[https:// | |
- | + | * 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. ATLAS Collaboration. https:// | ||
+ | * Search for new physics using unsupervised machine learning for anomaly detection in s√=13 TeV pp collision data recorded by the ATLAS detector at the LHC, ATL-COM-PHYS-2023-031 (March 2023) https:// | ||
+ | * ATLAS collaboration, | ||
+ | * ATLAS collaboration, | ||
+ | * ATLAS collaboration, | ||
+ | * S.V.Chekanov, | ||
+ | * S.V.Chekanov, | ||
+ | * S.Chekanov, R.Zhang, Enhancing the hunt for new phenomena in dijet final states using anomaly detection filters at the high-luminosity large Hadron Collider, Eur. Phys. J. Plus (2024) 139:237 | ||
+ | * Machine learning could help reveal undiscovered particles within data from the Large Hadron Collider, 2024, April [[https:// | ||
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 et al., Jas4pp. A Data-Analysis Framework for Physics and Detector Studies. APS April Meeting 2021, https:// | * S.Chekanov et al., Jas4pp. A Data-Analysis Framework for Physics and Detector Studies. APS April Meeting 2021, https:// | ||
* 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:// | * 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:// | ||
+ | * J.Crosby, " | ||
+ | * S.Chekanov, Event-based anomaly detection for new physics searches at the LHC using machine learning, APS April Meeting, Apr 8-14, 2022, https:// | ||
+ | * S.Chekanov, HepSim Monte Carlo repository and integration of its software with key4hep, FCC Software Meeting, May 30, 2023, https:// | ||
+ | * S.Chekanov et al, Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders, 2nd Future circular collider workshop (FCC-ee), Boston, MIT, March 24-28, 2024, (https:// | ||
+ | * S.Chekanov et al, ADFilter: Online tool for processing BSM models using trained deep learning autoencoder. ATLAS Machine Learning Workshop, | ||
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