| Both sides previous revision
Previous revision
Next revision
|
Previous revision
Next revision
Both sides next revision
|
hepsim:public [2022/04/11 16:33]
hepsim17 [HepSim in public talks] |
hepsim:public [2022/08/12 12:36]
hepsim17 [Articles] |
| * 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 | * 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 | * 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, https://arxiv.org/abs/2110.06277 | * 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. 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.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 | * 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. | * 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 ]] |
| |
| |
