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====== Public results ====== | ====== Public results ====== | ||
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* 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, S. Chekanov, W. Islam, d, A. Khanov, H. Meng, V. Pascuzzi, Signal optimization studies for dijet resonances in events with identified leptons using machine learning, June 2021, ATL-COM-PHYS-2021-391, | + | * S. Darmora |
+ | * S.V. Chekanov, W. Hopkins, Event-based anomaly detection for new physics searches at the LHC using machine learning, https:// | ||
+ | * S.Chekanov et al, " | ||
+ | * B. Nachman et al, Jets and Jet Substructure at Future Colliders, [[https:// | ||
+ | * F. Mokhtar et al., Explaining machine-learned particle-flow reconstruction, | ||
+ | * ATLAS Collaboration, | ||
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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:// | ||
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