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20192026
most citedApplications of Machine Learning to Lattice Quantum Field Theory

13 citations · 21 across the 14 of their papers we have counts for

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6 papers · 1 filter

hep-th2026

Toward Hamiltonian simulations of Maxwell-Chern-Simons theory: constant modes and gauge field truncation

Andrea Bulgarelli, Maria Cristina Diamantini, Nico Dichter +6

Maxwell-Chern-Simons (MCS) theory in dimensions provides a paradigmatic example of a topological gauge theory with both dynamical and topological degrees of freedom. Its Eucl…

hep-lat2026

A Finite-Volume Scheme for the Continuum Extrapolation of Lattice Step-Scaling in (2+1)D Hamiltonian U(1) Gauge Theory

Alessio Negro, Emil Otis Rosanowski, Lena Funcke +4

We propose a finite-volume scheme to perform controlled continuum extrapolations of the lattice step-scaling function, a key ingredient for determining the running coupling in a Ha…

cond-mat.str-el2026

Tackling the Sign Problem in the Doped Hubbard Model with Normalizing Flows

Dominic Schuh, Lena Funcke, Janik Kreit +2

The Hubbard model at finite chemical potential is a cornerstone for understanding doped correlated systems, but simulations are severely limited by the sign problem. In the auxilia…

hep-lat2026

Normalizing-flow-based density of states for (1+1)D U(1) lattice gauge theory with a -term

Simran Singh, Lena Funcke

A normalizing-flow-based implementation of the density-of-states approach has recently been used to successfully reconstruct the partition function of (1+1)D scalar lattice field t…

hep-lat2026

Hamiltonian Lattice QED with One and Two Flavors of Wilson Fermions: Topological Structure and Response

Sriram Bharadwaj, Emil Rosanowski, Simran Singh +5

The quantum simulation of topological phases in (2+1)D quantum electrodynamics with Wilson fermions provides a promising route toward realizing topological phenomena in near-term l…

cond-mat.str-el2026

Toward Scalable Normalizing Flows for the Hubbard Model

Janik Kreit, Andrea Bulgarelli, Lena Funcke +4

Normalizing flows have recently demonstrated the ability to learn the Boltzmann distribution of the Hubbard model, opening new avenues for generative modeling in condensed matter p…