高能物理张量网络：对Snowmass 2021的贡献
Tensor networks for High Energy Physics: contribution to Snowmass 2021
摘要：
张量网络方法在高能物理、凝聚态物理和量子信息科学中的作用日益重要。本文讨论了张量网络方法对高能物理中的格点场论、量子引力和量子信息系统的影响。这些工具将针对强相互作用系统的计算，这些系统在使用传统蒙特卡罗和其他重要性抽样方法时会因符号问题而变得困难。需要进一步开发方法和软件，以便对HEP产生重大影响。我们讨论的路线图，以执行量子色动力学（QCD）相关的计算在未来几年。这项研究是劳动密集型的，需要最先进的计算科学和计算机科学投入的发展和验证。我们简要讨论了与其他科学领域和工业的重叠。
英文摘要：
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.
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