Bulletin of the American Physical Society
APS April Meeting 2023
Volume 68, Number 6
Minneapolis, Minnesota (Apr 15-18)
Virtual (Apr 24-26); Time Zone: Central Time
Session C15: Mini-Symposium: AI for Nuclear and Particle PhysicsMini-Symposium
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Sponsoring Units: DNP DPF GDS Chair: Cristiano Fanelli, William & Mary, Jefferson Lab Room: Marquette VI - 2nd Floor |
Saturday, April 15, 2023 1:30PM - 2:06PM |
C15.00001: A.I. for particle physics Invited Speaker: David Lawrence TBD |
Saturday, April 15, 2023 2:06PM - 2:18PM |
C15.00002: Machine Learning for New Physics in B → K*l+l− Decays Shawn B Dubey, Thomas E Browder, Sven E Vahsen, Rahul Sinha, Saurabh Sandilya, Alexei Sibidanov, Rusa Mandal, Shahab Kohani In this work, we report the status of a neural network regression model |
Saturday, April 15, 2023 2:18PM - 2:30PM |
C15.00003: Machine Learning based Anomaly Detection for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter Kyungmin Park, Abhirami Harilal, Manfred Paulini, Michael Andrews Online Data Quality Monitoring (DQM) of the CMS electromagnetic calorimeter (ECAL) is a vital operational tool that allows ECAL experts to quickly identify, localize, and diagnose a broad range of detector issues that would otherwise prevent physics-quality data taking. Although the ECAL DQM system has been in operation since the start of the LHC and continuously updated to respond to new problems, it is challenging to anticipate anomalies in different shapes and sizes that had not been observed before. With the need for a more robust anomaly detection system, a real-time unsupervised machine learning based method is developed that can catch ECAL anomalies unseen in past data. After accounting for spatio-temporal deviations in the ECAL response, the Auto-Encoder based online DQM system is able to detect and localize anomalies with an estimated false discovery rate of 10^{-2} to 10^{-4} at 99% anomaly detection rate. We present anomaly detection results from the ECAL Barrel and Endcap regions, including new results from early LHC Run3 collision data. |
Saturday, April 15, 2023 2:30PM - 2:42PM |
C15.00004: Interpretability Inspires: How explainable AI helps improve Top Tagging Avik Roy, Mark S Neubauer, Ayush Khot Using state-of-the-art methods of explainable AI (XAI), we explore interpretability of deep neural network (DNN) models designed for identifying jets coming from top quark decay in the high energy proton-proton collisions at the Large Hadron Collider (LHC). We study the relative importance of low-level and high-level input features, variation of feature importance varies across different XAI metrics, and how latent space representations encode information and learn to correlate with physical quantities. We visualize the activity of hidden layers as to understand how DNNs relay information across the layers and how this understanding can help us to make such models significantly simpler by allowing effective model reoptimization and hyperparameter tuning. |
Saturday, April 15, 2023 2:42PM - 2:54PM |
C15.00005: A machine learning based approach to active magnetic field cancellation Matthew Morano The Neutron Electric Dipole Moment experiment at the Spallation Neutron Source |
Saturday, April 15, 2023 2:54PM - 3:06PM Author not Attending |
C15.00006: Machine learning-assisted measurement of azimuthal angular asymmetry of soft gluon radiation in deep-inelastic scattering with the H1 detector Fernando Torales Acosta At leading order in positron-proton collisions, a lepton scatters off a quark through virtual photon exchange, producing a quark jet and scattered lepton in the final state. The total transverse momentum of the system is typically small, however deviations from zero can be attributed to perturbative initial and final state radiations in the form of soft gluon radiation when the transverse momentum difference, $lvert vec{P}_perp
vert $, is much greater than the total transverse momentum of the system, $lvert vec{q}_perp
vert$. The soft gluon radiation comes only from the jet, and should result in a measurable azimuthal asymmetry between $vec{P}_perp$ and $vec{q}_perp$. Quantifying the contribution of soft gluon radiation to this asymmetry should serve as a novel test of perturbative QCD as well as an important background estimation for measurements of the lepton-jet imbalance that have recently garnered intense investigation. |
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