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Related papers: Lecture Notes on Normalizing Flows for Lattice Qua…

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We discuss the application of normalizing flows to bosonic lattice field theories with real-time sign problems. A normalizing flow, once it is found for such a lattice field theory, is guaranteed to solve its sign problem. We argue for the…

High Energy Physics - Lattice · Physics 2022-01-03 Yukari Yamauchi , Scott Lawrence

Numerical simulations have become an important tool to understand and predict non-perturbative phenomena in particle physics. In this article we attempt to present a general overview over the field. First, the basic concepts of lattice…

High Energy Physics - Lattice · Physics 2010-12-17 F. Karsch , E. Laermann

We propose a novel machine learning method for sampling from the high-dimensional probability distributions of Lattice Field Theories, which is based on a single neural ODE layer and incorporates the full symmetries of the problem. We test…

High Energy Physics - Lattice · Physics 2023-12-21 Mathis Gerdes , Pim de Haan , Corrado Rainone , Roberto Bondesan , Miranda C. N. Cheng

A hallmark of the computational campaign in nuclear and particle physics is the lattice-gauge-theory program. It continues to enable theoretical predictions for a range of phenomena in nature from the underlying Standard Model. The…

High Energy Physics - Lattice · Physics 2025-09-23 Zohreh Davoudi

We discuss Hamiltonian learning in quantum field theories as a protocol for systematically extracting the operator content and coupling constants of effective field theory Hamiltonians from experimental data. Learning the Hamiltonian for…

Normalizing Flows are a promising new class of algorithms for unsupervised learning based on maximum likelihood optimization with change of variables. They offer to learn a factorized component representation for complex nonlinear data and,…

Machine Learning · Computer Science 2020-02-17 Reuben Feinman , Nikhil Parthasarathy

After a brief introduction to the statistical description of data, these lecture notes focus on quantum field theories as they emerge from lattice models in the critical limit. For the simulation of these lattice models, Markov chain…

High Energy Physics - Lattice · Physics 2007-11-20 Kurt Langfeld

These are introductory lecture notes aimed at beginning graduate students covering fundamental concepts and ideas behind the renormalisation group. Our main goal is to motivate it and then explore its consequences, in the context of quantum…

High Energy Physics - Theory · Physics 2019-10-28 João F. Melo

We study the consequences of mode-collapse of normalizing flows in the context of lattice field theory. Normalizing flows allow for independent sampling. For this reason, it is hoped that they can avoid the tunneling problem of local-update…

High Energy Physics - Lattice · Physics 2023-11-06 Kim A. Nicoli , Christopher J. Anders , Tobias Hartung , Karl Jansen , Pan Kessel , Shinichi Nakajima

Normalizing flows are a class of deep generative models that provide a promising route to sample lattice field theories more efficiently than conventional Monte Carlo simulations. In this work we show that the theoretical framework of…

High Energy Physics - Lattice · Physics 2022-07-07 Michele Caselle , Elia Cellini , Alessandro Nada , Marco Panero

The so-called trivializing flows were proposed to speed up Hybrid Monte Carlo simulations, where the Wilson flow was used as an approximation of a trivializing map, a transformation of the gauge fields which trivializes the theory. It was…

High Energy Physics - Lattice · Physics 2023-10-06 David Albandea , Luigi Del Debbio , Pilar Hernández , Richard Kenway , Joe Marsh Rossney , Alberto Ramos

We review the gradient flow for gauge and fermion fields and its applications to lattice gauge theory computations. Using specific examples, we discuss the interplay between perturbative and non-perturbative calculations in the context of…

High Energy Physics - Lattice · Physics 2023-01-19 Andrea Shindler

I review the strategies which have been developped in recent years to solve the non-perturbative renormalization problem in lattice field theories. Although the techniques are general, the focus will be on applications to lattice QCD. I…

High Energy Physics - Lattice · Physics 2009-10-31 Stefan Sint

The problem of obtaining a realistic, relativistic description of a quantum system is discussed in the context of a simple (light-cone) lattice field theory. A natural stochastic model is proposed which, although non-local, is relativistic…

High Energy Physics - Theory · Physics 2016-09-06 T. M. Samols

Quantum computing holds great promise to accelerate scientific computations in fluid dynamics and other classical physical systems. While various quantum algorithms have been proposed for linear flows, developing quantum algorithms for…

Fluid Dynamics · Physics 2025-02-25 Boyuan Wang , Zhaoyuan Meng , Yaomin Zhao , Yue Yang

This paper fires the opening salvo in the systematic construction of the lattice-continuum correspondence, a precise dictionary that describes the emergence of continuum quantum theories from finite, nonperturbatively defined models…

High Energy Physics - Theory · Physics 2021-08-31 Djordje Radicevic

These lecture notes provide a relatively self-contained introduction to field theoretic methods employed in the study of classical and quantum phase transitions.

Statistical Mechanics · Physics 2010-09-09 Flavio S. Nogueira

Normalizing flows have recently been applied to the problem of accelerating Markov chains in lattice field theory. We propose a generalization of normalizing flows that allows them to applied to theories with a sign problem. These complex…

High Energy Physics - Lattice · Physics 2022-05-26 Scott Lawrence , Yukari Yamauchi

The quantum theory of fields is largely based on studying perturbations around non-interacting, or free, field theories, which correspond to a collection of quantum-mechanical harmonic oscillators. The quantum theory of an ordinary fluid is…

High Energy Physics - Theory · Physics 2015-04-24 Ben Gripaios , Dave Sutherland

Generative models, particularly normalizing flows, have shown exceptional performance in learning probability distributions across various domains of physics, including statistical mechanics, collider physics, and lattice field theory. In…

Strongly Correlated Electrons · Physics 2025-01-14 Dominic Schuh , Janik Kreit , Evan Berkowitz , Lena Funcke , Thomas Luu , Kim A. Nicoli , Marcel Rodekamp