Tensor networks for High Energy Physics: contribution to Snowmass 2021

Bibliographic Details
Title: Tensor networks for High Energy Physics: contribution to Snowmass 2021
Authors: Meurice, Yannick, Osborn, James C., Sakai, Ryo, Unmuth-Yockey, Judah, Catterall, Simon, Somma, Rolando D.
Publication Year: 2022
Collection: High Energy Physics - Lattice
High Energy Physics - Theory
Subject Terms: High Energy Physics - Lattice, High Energy Physics - Theory
More Details: Tensor network methods are becoming increasingly important for high-energy physics, condensed matter physics and quantum information science (QIS). We discuss the impact of tensor network methods on lattice field theory, quantum gravity and QIS in the context of High Energy Physics (HEP). These tools will target calculations for strongly interacting systems that are made difficult by sign problems when conventional Monte Carlo and other importance sampling methods are used. Further development of methods and software will be needed to make a significant impact in HEP. We discuss the roadmap to perform quantum chromodynamics (QCD) related calculations in the coming years. The research is labor intensive and requires state of the art computational science and computer science input for its development and validation. We briefly discuss the overlap with other science domains and industry.
Comment: Contribution to Snowmass 2021, preliminary version
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2203.04902
Accession Number: edsarx.2203.04902
Database: arXiv
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