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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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15 papers · 1 filter

cond-mat.soft2026

Multivariate hyperdensity functional theory for inhomogeneous equilibrium fluids: From first principles to simulation-based machine learning

Florian Sammüller, Matthias Schmidt

Hyperdensity functional theory facilitates the investigation of the equilibrium behavior of a general order parameter or statistical mechanical observable in spatially inhomogeneou…

cond-mat.soft2026

Entropy power functional theory for Brownian many-body dynamics

Matthias Schmidt

We present a formally exact variational scheme for the overdamped Brownian dynamics of pairwise interacting many-body systems in general spatiotemporal nonequilibrium. A joint free…

cond-mat.soft2026

Entropy functional universality: Correlation, response, many-body interaction, multi-component, quantum, hyperfunctional, and Ornstein-Zernike structure

Matthias Schmidt

We give a comprehensive account of the recent entropy functional theory for the equilibrium statistical mechanics of classical many-body systems (arXiv:2606.28240). The approach is…

cond-mat.soft2026

Entropy functional theory for inhomogeneous fluids

Matthias Schmidt

We present an exact variational scheme for the physics of inhomogeneous classical fluids in thermal equilibrium. A joint metadensity minimization principle is proven for the one-bo…

cond-mat.soft2026

Nonequilibrium scaling of drag forces in counterdriven fluid mixtures

Jonas Köglmayr, Florian Sammüller, Matthias Schmidt

We address the effective nonequilibrium drag force field that emerges from the microscopic interparticle interactions in steady states of counterdriven binary fluid mixtures. Using…

cond-mat.soft2026★ 3 cited

Metadensity functional learning for classical fluids: Regularizing with pair correlations

Stefanie M. Kampa, Florian Sammüller, Matthias Schmidt

We investigate and exploit consequences of the recent neural metadensity functional theory [Kampa et al., Phys. Rev. Lett. 134, 107301 (2025), 10.1103/PhysRevLett.134.107301] for d…

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.soft2024★ 13 cited

Why hyperdensity functionals describe any equilibrium observable

Florian Sammüller, Matthias Schmidt

We give an introductory account of the recent hyperdensity functional theory for the equilibrium statistical mechanics of soft matter systems [F. Sammüller et al., Phys. Rev. Lett.…

cond-mat.soft2024★ 11 cited

Metadensity functional theory for classical fluids: Extracting the pair potential

Stefanie M. Kampa, Florian Sammüller, Matthias Schmidt +1

The excess free energy functional of classical density functional theory depends upon the type of fluid model, specifically on the choice of (pair) potential, is unknown in general…

cond-mat.soft2024★ 17 cited

Neural density functional theory of liquid-gas phase coexistence

Florian Sammüller, Matthias Schmidt, Robert Evans

We use supervised machine learning together with the concepts of classical density functional theory to investigate the effects of interparticle attraction on the pair structure, t…

cond-mat.soft2024★ 17 cited

Neural density functionals: Local learning and pair-correlation matching

Florian Sammüller, Matthias Schmidt

Recently Dijkman et al. (arXiv:2403.15007) proposed training classical neural density functionals via bulk pair-correlation matching. We show their method to be an efficient regula…

cond-mat.soft2024★ 21 cited

Hyper-density functional theory of soft matter

Florian Sammüller, Silas Robitschko, Sophie Hermann +1

We present a scheme for investigating arbitrary thermal observables in spatially inhomogeneous equilibrium many-body systems. Extending the grand canonical ensemble yields any give…

cond-mat.soft2024★ 11 cited

Noether invariance theory for the equilibrium force structure of soft matter

Sophie Hermann, Florian Sammüller, Matthias Schmidt

We give details and derivations for the Noether invariance theory that characterizes the spatial equilibrium structure of inhomogeneous classical many-body systems, as recently pro…

cond-mat.soft2023★ 22 cited

Why neural functionals suit statistical mechanics

Florian Sammüller, Sophie Hermann, Matthias Schmidt

We describe recent progress in the statistical mechanical description of many-body systems via machine learning combined with concepts from density functional theory and many-body…