activity
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

collaborators

44 papers

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…

quant-ph2026

String dynamics of a (2+1)D U(1) quantum link model on a digital quantum computer

Anthony Gandon, Alessandro Mariani, Debasish Banerjee +5

The (2+1)D U(1) pure gauge theory always exists in the confining phase, with strings of non-zero string tension giving a characteristic linear potential between static charges. Thi…

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…