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hepsim:public [2023/08/08 12:48]
hepsim17 [Articles] |
hepsim:public [2024/04/17 12:30] (current)
hepsim17 [Articles] |
| * ATLAS collaboration, Search for new phenomena in multi-body invariant masses in events with at least one isolated lepton and two jets using 13 TeV proton–proton collision data collected by the ATLAS detector, J. High Energ. Phys. 2023, 202 (2023). https://doi.org/10.1007/JHEP07(2023)202 | * ATLAS collaboration, Search for new phenomena in multi-body invariant masses in events with at least one isolated lepton and two jets using 13 TeV proton–proton collision data collected by the ATLAS detector, J. High Energ. Phys. 2023, 202 (2023). https://doi.org/10.1007/JHEP07(2023)202 |
| * S.V.Chekanov, R.Zhang, Boosting sensitivity to new physics with unsupervised anomaly detection in dijet resonance search, ANL-HEP-183852, https://arxiv.org/abs/2308.02671 (arXiv:2308.02671) | * S.V.Chekanov, R.Zhang, Boosting sensitivity to new physics with unsupervised anomaly detection in dijet resonance search, ANL-HEP-183852, https://arxiv.org/abs/2308.02671 (arXiv:2308.02671) |
| | * S.V.Chekanov, S.Eno, S.Magill, C.Palmer, L.Wu, Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders, ANL-HEP-186226, [[https://arxiv.org/abs/2311.03539|arXiv:2311.03539]] |
| | * 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://www.anl.gov/article/machine-learning-could-help-reveal-undiscovered-particles-within-data-from-the-large-hadron-collider|ANL press release]] [[https://www.newswise.com/doescience/machine-learning-could-help-reveal-undiscovered-particles-within-data-from-the-large-hadron-collider|newswise]] [[https://phys.org/news/2024-04-machine-reveal-undiscovered-particles-large.html|Phys.Org]] |
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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. |
| * 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 | * 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 |
| * S.Chekanov, HepSim Monte Carlo repository and integration of its software with key4hep, FCC Software Meeting, May 30, 2023, https://indico.cern.ch/event/1283173/, | * S.Chekanov, HepSim Monte Carlo repository and integration of its software with key4hep, FCC Software Meeting, May 30, 2023, https://indico.cern.ch/event/1283173/, |
| | * 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://indico.mit.edu/event/876/) |
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