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20232026
most citedWhy neural functionals suit statistical mechanics

22 citations · 158 across the 21 of their papers we have counts for

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5 papers · 1 filter

quant-ph2025

Quantum statistical mechanical gauge invariance

Johanna Müller, Matthias Schmidt

We address gauge invariance in the statistical mechanics of quantum many-body systems. The gauge transformation acts on the position and momentum degrees of freedom and it is repre…

cond-mat.stat-mech2025★ 6 cited

Gauge invariance and hyperforce correlation theory for equilibrium fluid mixtures

Joshua Matthes, Silas Robitschko, Johanna Müller +3

We formulate gauge invariance for the equilibrium statistical mechanics of classical multi-component systems. Species-resolved phase space shifting constitutes a gauge transformati…

cond-mat.soft2025★ 9 cited

Learning the bulk and interfacial physics of liquid-liquid phase separation with neural density functionals

Silas Robitschko, Florian Sammüller, Matthias Schmidt +1

We use simulation-based supervised machine learning and classical density functional theory to investigate bulk and interfacial phenomena associated with phase coexistence in binar…

cond-mat.soft2025★ 3 cited

Determining the chemical potential via universal density functional learning

Florian Sammüller, Matthias Schmidt

We demonstrate that the machine learning of density functionals allows one to determine simultaneously the equilibrium chemical potential across simulation datasets of inhomogeneou…

cond-mat.stat-mech2025

Dynamical gauge invariance of statistical mechanics

Johanna Müller, Florian Sammüller, Matthias Schmidt

We investigate gauge invariance against phase space shifting in nonequilibrium systems, as represented by time-dependent many-body Hamiltonians that drive an initial ensemble out o…