Applications of Machine Learning to Lattice Quantum Field Theory
It addresses the challenge of integrating machine learning into lattice quantum field theory for researchers in physics and computational science, but it is incremental as it focuses on outlining requirements rather than presenting new results.
The paper discusses the potential of applying machine learning to lattice quantum field theory, emphasizing the need for new strategies to fully exploit this potential.
There is great potential to apply machine learning in the area of numerical lattice quantum field theory, but full exploitation of that potential will require new strategies. In this white paper for the Snowmass community planning process, we discuss the unique requirements of machine learning for lattice quantum field theory research and outline what is needed to enable exploration and deployment of this approach in the future.