Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models

Quantum Fields as Deep Learning

(2020) Jae-Weon Lee   JOURNAL OF THE KOREAN PHYSICAL SOCIETY

Equivariant Flow-Based Sampling for Lattice Gauge Theory

(2020) Gurtej Kanwar et al.   PHYSICAL REVIEW LETTERS

Tensor renormalization group approach to four-dimensional complex ϕ4 theory at finite density

(2020) Shinichiro Akiyama et al.   JOURNAL OF HIGH ENERGY PHYSICS

Solving Statistical Mechanics Using Variational Autoregressive Networks

(2019) Dian Wu et al.   PHYSICAL REVIEW LETTERS

Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning

(2019) Frank Noé et al.   SCIENCE

Neural Importance Sampling

(2019) Thomas Müller et al.   ACM TRANSACTIONS ON GRAPHICS

Heavy Ion Collisions: The Big Picture and the Big Questions

(2018) Wit Busza et al.   Annual Review of Nuclear and Particle Science

Equation of state of the SU(3) Yang–Mills theory: A precise determination from a moving frame

(2017) Leonardo Giusti et al.   PHYSICS LETTERS B

Thermodynamics ofSU(3)gauge theory from gradient flow on the lattice

(2014) Masayuki Asakawa et al.   PHYSICAL REVIEW D

Equation of State of a Relativistic Theory from a Moving Frame

(2014) Leonardo Giusti et al.   PHYSICAL REVIEW LETTERS

The QCD equation of state from the lattice

(2012) Owe Philipsen   PROGRESS IN PARTICLE AND NUCLEAR PHYSICS