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20182026
most citedFlow-based generative models for Markov chain Monte Carlo in lattice field theory

222 citations · 1.1k across the 42 of their papers we have counts for

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39 papers · 1 filter

hep-lat2026

Complex-momentum form factors from lattice QCD

Maxwell T. Hansen, Gurtej Kanwar

We demonstrate that form factors evaluated with momenta analytically continued into the complex plane can be accessed directly from position-space Euclidean correlators such as tho…

hep-lat2026

Learning the generating functional for variance reduction in lattice QCD

Ryan Abbott, Yang Fu, Daniel C. Hackett +3

The generating functional in quantum field theory provides the natural framework for constructing correlation functions as derivatives with respect to source operators. We present…

hep-lat2026

Normalizing flows for all-orders QED corrections in lattice field theory

Nils Hermansson-Truedsson, Gurtej Kanwar

This work develops a framework to apply normalizing-flow transformations of field configurations for all-orders Quantum Electrodynamics (QED) corrections in lattice field theory. T…

hep-lat2026

Variance reduction in lattice QCD observables via normalizing flows

Ryan Abbott, Denis Boyda, Yang Fu +5

Normalizing flows can be used to construct unbiased, reduced-variance estimators for lattice field theory observables that are defined by a derivative with respect to action parame…

hep-lat2026

A Monte Carlo estimator of flow fields for sampling and noise problems

Michael S. Albergo, Gurtej Kanwar

Learned field transformations may help address ubiquitous critical slowing down and signal-to-noise problems in lattice field theory. In the context of an annealed sequence of dist…

hep-lat2025

HLbL contribution to the muon g-2 using twisted-mass fermions at the physical point

N. Kalntis, G. Kanwar, M. Petschlies +2

We present updated results for the hadronic light-by-light (HLbL) contribution to the muon anomalous magnetic moment. The calculations are based on ETMC's Wilson-clover…

hep-lat2025

Spectral Diffusion for Sampling on

Gurtej Kanwar, Octavio Vega

Although ensemble generation remains a central challenge in lattice field theory simulations, recent advances in generative modeling may offer a path to accelerated sampling in the…

hep-lat2025

Progress in Normalizing Flows for 4d Gauge Theories

Ryan Abbott, Denis Boyda, Daniel C. Hackett +4

Normalizing flows have arisen as a tool to accelerate Monte Carlo sampling for lattice field theories. This work reviews recent progress in applying normalizing flows to 4-dimensio…

hep-lat2024

Hadronic light-by-light contribution to the muon using twisted-mass fermions

Nikolaos Kalntis, Gurtej Kanwar, Marcus Petschlies +2

We report on our preliminary results from the lattice-QCD computation of the hadronic light-by-light (HLbL) contribution to the anomalous magnetic moment of the muon. We use twiste…

hep-lat2024

Exploring gauge-fixing conditions with gradient-based optimization

William Detmold, Gurtej Kanwar, Yin Lin +2

Lattice gauge fixing is required to compute gauge-variant quantities, for example those used in RI-MOM renormalization schemes or as objects of comparison for model calculations. R…

hep-lat2024

Practical applications of machine-learned flows on gauge fields

Ryan Abbott, Michael S. Albergo, Denis Boyda +5

Normalizing flows are machine-learned maps between different lattice theories which can be used as components in exact sampling and inference schemes. Ongoing work yields increasin…

hep-lat2024

Multiscale Normalizing Flows for Gauge Theories

Ryan Abbott, Michael S. Albergo, Denis Boyda +5

Scale separation is an important physical principle that has previously enabled algorithmic advances such as multigrid solvers. Previous work on normalizing flows has been able to…

hep-lat2024★ 1 cited

Multi-particle interpolating operators in quantum field theories with cubic symmetry

William Detmold, William I. Jay, Gurtej Kanwar +2

Numerical studies of lattice quantum field theories are conducted in finite spatial volumes, typically with cubic symmetry in the spatial coordinates. Motivated by these studies, t…

hep-lat2024

Flow-based sampling for lattice field theories

Gurtej Kanwar

Critical slowing down and topological freezing severely hinder Monte Carlo sampling of lattice field theories as the continuum limit is approached. Recently, significant progress h…

hep-lat2024

Applications of flow models to the generation of correlated lattice QCD ensembles

Ryan Abbott, Aleksandar Botev, Denis Boyda +7

Machine-learned normalizing flows can be used in the context of lattice quantum field theory to generate statistically correlated ensembles of lattice gauge fields at different act…

hep-lat2023★ 3 cited

Broken Symmetry and Fractionalized Flux Strings in a Staggered U(1) Pure Gauge Theory

A. Banerjee, D. Banerjee, G. Kanwar +3

Inspired by self-adjoint extensions of the electric field operator in the Hamiltonian formalism, we extend the Wilsonian framework of Abelian lattice gauge theory by introducing a…

hep-lat2023★ 31 cited

Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics

Kyle Cranmer, Gurtej Kanwar, Sébastien Racanière +2

Sampling from known probability distributions is a ubiquitous task in computational science, underlying calculations in domains from linguistics to biology and physics. Generative…

hep-lat2023★ 1 cited

Signal-to-noise improvement through neural network contour deformations for 3D lattice gauge theory

William Detmold, Gurtej Kanwar, Yin Lin +2

Complex contour deformations of the path integral have been demonstrated to significantly improve the signal-to-noise ratio of observables in previous studies of two-dimensional ga…

hep-lat2023★ 13 cited

Pion Transition Form Factor from Twisted-Mass Lattice QCD and the Hadronic Light-by-Light -pole Contribution to the Muon

C. Alexandrou, S. Bacchio, G. Bergner +14

The neutral pion generates the leading pole contribution to the hadronic light-by-light tensor, which is given in terms of the nonperturbative transition form factor $\mathcal{F}_{…

hep-lat2023★ 10 cited

Normalizing flows for lattice gauge theory in arbitrary space-time dimension

Ryan Abbott, Michael S. Albergo, Aleksandar Botev +11

Applications of normalizing flows to the sampling of field configurations in lattice gauge theory have so far been explored almost exclusively in two space-time dimensions. We repo…

hep-lat2022★ 1 cited

Pseudoscalar-pole contributions to the muon at the physical point

Sebastian Burri, Gurtej Kanwar, Constantia Alexandrou +14

Pseudoscalar-pole diagrams are an important component of estimates of the hadronic light-by-light (HLbL) contribution to the muon . We report on our computation of the transit…

hep-lat2022

Confined Charged Particles in C-periodic Volumes

G. Kanwar, A. Mariani, J. C. Pinto Barros +1

Charged particles in an Abelian Coulomb phase are non-local infraparticles that are surrounded by a cloud of soft photons which extends to infinity. Gauss' law prevents the existen…

hep-lat2022

A New Type of Lattice Gauge Theory through Self-adjoint Extensions

A. Banerjee, D. Banerjee, G. Kanwar +3

A generalization of Wilsonian lattice gauge theory may be obtained by considering the possible self-adjoint extensions of the electric field operator in the Hamiltonian formalism.…

hep-lat2022★ 7 cited

Sampling QCD field configurations with gauge-equivariant flow models

Ryan Abbott, Michael S. Albergo, Aleksandar Botev +11

Machine learning methods based on normalizing flows have been shown to address important challenges, such as critical slowing-down and topological freezing, in the sampling of gaug…