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 G03: Computational Approaches in Hadronic PhysicsInvited
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Sponsoring Units: GHP Chair: Christopher Monahan, William & Mary Room: MG Salon B - 3rd Floor |
Sunday, April 16, 2023 10:45AM - 11:21AM |
G03.00001: Machine Learning and Artificial Intelligence in Hadronic Physics Invited Speaker: Cristiano Fanelli Machine learning (ML) and artificial intelligence (AI) techniques are now actively used in multiple aspects of hadronic physics, both theoretically and experimentally, the latter being the focus of this talk. ML and AI target practically all facets of QCD theory and contribute to enhancing the precision of measurements in hadronic physics, detecting the nature of measured events, explaining the underlying mechanisms from final distribution of particles, and speeding up theoretical calculations. In experiments, ML/AI are largely used for particle reconstruction, identification, event classification, and spectroscopy, and will be used in nearly every system of future QCD frontier experiments, such as the Electron Ion Collider; AI is also increasingly being used for autonomous control and experimentation, present experiment operations and calibrations, and the design of future QCD experiments. The development of next-generation data acquisition systems that stream all data from each detector to a data center to be analyzed, tagged, and filtered can further increase the implementation of ML/AI-based solutions for near real-time analysis, resulting in a shorter time to produce scientific results. This talk will provide you with a global yet non-exhaustive picture of ML/AI activities in experimental hadronic physics, the needs highlighted by our community to leverage ML/AI for QCD research, as well as potential future prospects for ML/AI applications in hadronic physics. |
Sunday, April 16, 2023 11:21AM - 11:57AM |
G03.00002: Bayesian inference in hadronic physics: examples from heavy ion physics Invited Speaker: Jean Francois Paquet Colliding large nuclei at velocities close to the speed of light produces a plasma of strongly interacting nuclear matter known as quark-gluon plasma. This nuclear plasma can be characterized by macroscopic properties such as its equation of state and viscosity. Bayesian inference provides an important tool to constrain systematically these properties of nuclear matter with measurements from the Relativistic Heavy Ion Collider and the Large Hadron Collider. I will survey different use of Bayesian inference in heavy-ion collisions, including applications of transfer learning, model comparison, closure tests, model averaging and stochastic emulator uncertainty optimization. |
Sunday, April 16, 2023 11:57AM - 12:33PM |
G03.00003: Quantum computing in hadronic physics Invited Speaker: Sofia Quaglioni Together with major theoretical breakthroughs, computing and simulations play an increasingly essential role in meeting the challenges and realizing the full potential of current and future experimental programs in nuclear physics. With the exponential increase in computing power enabled by the superposition and entanglement properties of quantum bits, quantum computing and simulations open the opportunity for potentially transformational, exact predictions of nuclear phenomena, ranging from the structure and interactions of hadronic matter at the most fundamental level, to stellar explosions. In this talk, I will provide an overview of recent developments and future opportunities in leveraging emerging quantum computing and quantum simulation platforms to open new horizons in nuclear theory research. |
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