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hepsim:public [2023/05/22 12:36] hepsim17 [Articles] |
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* 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 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:// | * 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. Search for new phenomena in two-body invariant mass distributions using unsupervised machine learning for anomaly detection at s√=13 TeV with the ATLAS detector. ATLAS-COM-CONF-2023-022 (https:// | + | * ATLAS collaboration, Search for new phenomena in two-body invariant mass distributions using unsupervised machine learning for anomaly detection at s√=13 TeV with the ATLAS detector. ATLAS-COM-CONF-2023-022 (https:// |
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+ | * 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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* J.Crosby, " | * 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, 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:// | ||
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