In this review, I recall the nature and the inevitability of the" sign problem" which plagues
attempts to simulate lattice QCD at finite baryon density. I present the main approaches used …

The successes and limitations of statistical sampling for a sequence of models studied in the
context of lattice QCD are discussed and the need for new methods to deal with finite …

We define a class of machine-learned flow-based sampling algorithms for lattice gauge
theories that are gauge invariant by construction. We demonstrate the application of this …

A Markov chain update scheme using a machine-learned flow-based generative model is
proposed for Monte Carlo sampling in lattice field theories. The generative model may be …

Featuring detailed explanations of the major algorithms used in quantum Monte Carlo
simulations, this is the first textbook of its kind to provide a pedagogical overview of the field …

A detailed description is provided of a new worm algorithm, enabling the accurate
computation of thermodynamic properties of quantum many-body systems in continuous …

These lecture notes contain an elementary introduction to lattice QCD at nonzero chemical
potential. Topics discussed include chemical potential in the continuum and on the lattice; …

Algorithms based on normalizing flows are emerging as promising machine learning
approaches to sampling complicated probability distributions in a way that can be made …

Quantum field theories (QFTs) at finite densities of matter generically involve complex
actions. Standard Monte Carlo simulations based upon importance sampling, which have …

Abstract We study the Berezinskii-Kosterlitz-Thouless transition in a weakly interacting 2D
quantum Bose gas using the concept of universality and numerical simulations of the …