
Machine-learning-based sampling in lattice QCD
Despite being in the early days, machine-learning-based sampling developped for lattice QCD simulations promises advances not only in physics, but also in machine learning.
Despite being in the early days, machine-learning-based sampling developped for lattice QCD simulations promises advances not only in physics, but also in machine learning.
Across thermodynamics, systems exchange quantities such as energy and particles. What if the quantities are represented by operators that fail to commute with each other? This Perspective surveys the implications for quantum thermodynamics and adjacent fields.