Editorial: Efficient AI in particle physics and astrophysics

Front Artif Intell. 2022 Sep 30:5:999173. doi: 10.3389/frai.2022.999173. eCollection 2022.

Javier Duarte¹, Mia Liu², Jennifer Ngadiuba³, Elena Cuoco^{4

5}, Jesse Thaler^{6

7}

¹ Department of Physics, University of California, San Diego, La Jolla, CA, United States.
² Department of Physics, Purdue University, West Lafayette, IN, United States.
³ Particle Physics Division, Fermi National Accelerator Laboratory, Batavia, IL, United States.
⁴ European Gravitational Observatory, Cascina, Italy.
⁵ Scuola Normale Superiore, Pisa, Italy.
⁶ Center for Theoretical Physics, Massachusetts Institute of Technology, Cambridge, MA, United States.
⁷ The NSF AI Institute for Artificial Intelligence and Fundamental Interactions, Cambridge, MA, United States.

No abstract available

Keywords: FPGA; efficiency; high energy physics; neural network; particle astrophysics; physics-inspired; pruning; quantization.

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