Hybrid Quantum-Classical Simulation for Non-Perturbative Jet Production Dynamics at Scale with CUDA Quantum
ORAL
Abstract
As a significant step towards developing this approach, we present our findings from GPU-driven hybrid quantum-classical simulations of the massive Schwinger model in the presence of a pair of hard external particles. It produces a set-up similar to the one leading to the production of jets in high-energy collisions. We investigate how the presence of these propagating jets affects the vacuum chiral condensate, as well as the quantum entanglement between the jets as they fragment. This work is performed on NERSC's Perlmutter system leveraging the multi-node multi-GPU architecture using NVIDIA’s CUDA Quantum, which is a software development kit for quantum and integrated quantum-classical programming.
* This work was supported by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Co-design Center for Quantum Advantage (C2QA) under Contract No.DE-SC0012704 (AF, KI, DK, VK), the U.S. Department of Energy, Office of Science, Office of Nuclear Physics, Grants Nos. DE-FG88ER41450 (DF, DK, SS) and DE-SC0012704 (AF, DK, KY), and Tsinghua University under grant no. 53330500923 (SS). This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award NERSC DDR-ERCAP0022229. This work is performed on NERSC's Perlmutter system leveraging the multi-node multi-GPU architecture using NVIDIA's CUDA Quantum.
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Publication: Phys. Rev. Lett. 131 (2023) 021902
Presenters
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Kazuki Ikeda
Stony Brook University
Authors
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Kazuki Ikeda
Stony Brook University
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Pooja Rao
Nvidia
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Adrien Florio
Brookhaven National Laboratory, Stonybrook University
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David Frenklakh
Stony Brook University
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Dmitri E Kharzeev
State Univ of NY - Stony Brook
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Jin-Sung Kim
NVIDIA Corporation
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Vladimir Korepin
Stony Brook University
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Alex McCaskey
NVIDIA, Nvidia
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Shuzhe Shi
Tsinghua University
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Yu Kwangmin
Brookhaven National Laboratory