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Machine learning methods for solving the equations of dynamical mean-field theory are developed. The method is demonstrated on the three dimensional Hubbard model. The key technical issues are defining a mapping of an input function to an…

Strongly Correlated Electrons · Physics 2015-07-01 Louis-François Arsenault , O. Anatole von Lilienfeld , Andrew J. Millis

Classical density functional theory (DFT) provides an exact variational framework for determining the equilibrium properties of inhomogeneous fluids. We report a generalization of DFT to treat the non-equilibrium dynamics of classical…

Soft Condensed Matter · Physics 2013-09-06 Matthias Schmidt , Joseph M. Brader

The derivation of the state of the art tensorial versions of Fundamental Measure Theory (a form of classical Density Functional Theory for hard spheres) are re-examined in the light of the recently introduced concept of global stability of…

Statistical Mechanics · Physics 2021-01-04 James F. Lutsko

We use density-matrix renormalization group, applied to a one-dimensional model of continuum Hamiltonians, to accurately solve chains of hydrogen atoms of various separations and numbers of atoms. We train and test a machine-learned…

Strongly Correlated Electrons · Physics 2016-12-28 Li Li , Thomas E. Baker , Steven R. White , Kieron Burke

The classical Density Functional Theory (DFT) is introduced as an application of entropic inference for inhomogeneous fluids at thermal equilibrium. It is shown that entropic inference reproduces the variational principle of DFT when…

Statistical Mechanics · Physics 2021-09-14 Ahmad Yousefi , Ariel Caticha

We analyze the structure of the Fundamental Measure Theory for the free energy density functional of hard sphere mixtures. A comparative study of the different versions of the theory, and other density functional approaches, is done in…

Soft Condensed Matter · Physics 2009-11-07 Jose A. Cuesta , Yuri Martinez-Raton , Pedro Tarazona

With the growth of computational resources, the scope of electronic structure simulations has increased greatly. Artificial intelligence and robust data analysis hold the promise to accelerate large-scale simulations and their analysis to…

Materials Science · Physics 2023-07-27 Lenz Fiedler , Karan Shah , Michael Bussmann , Attila Cangi

We report a theoretical and simulation study of the drying and wetting phase transitions of a truncated Lennard-Jones fluid at a flat structureless wall. Binding potential calculations predict that the nature of these transitions depends on…

Statistical Mechanics · Physics 2017-09-13 Robert Evans , Maria C. Stewart , Nigel B. Wilding

Using a dynamical density functional theory we analyze the density profile of a colloidal liquid near a wall under shear flow. Due to the symmetries of the system considered, the naive application of dynamical density functional theory does…

Soft Condensed Matter · Physics 2015-05-20 J. M. Brader , M. Krüger

Classical dynamical density functional theory (DDFT) is one of the cornerstones of modern statistical mechanics. It is an extension of the highly successful method of classical density functional theory (DFT) to nonequilibrium systems.…

Soft Condensed Matter · Physics 2020-12-29 Michael te Vrugt , Hartmut Löwen , Raphael Wittkowski

A scheme within density functional theory is proposed that provides a practical way to generalize to unrestricted geometries the method applied with some success to layered geometries [H. Rydberg, et al., Phys. Rev. Lett. 91, 126402…

Materials Science · Physics 2009-11-10 M. Dion , H. Rydberg , E. Schroder , D. C. Langreth , B. I. Lundqvist

This work maps deep neural networks to classical Ising spin models, allowing them to be described using statistical thermodynamics. The density of states shows that structures emerge in the weights after they have been trained --…

Statistical Mechanics · Physics 2022-09-20 Dusan Stosic , Darko Stosic , Borko Stosic

A geometry-based density functional theory is presented for mixtures of hard spheres, hard needles and hard platelets; both the needles and the platelets are taken to be of vanishing thickness. Geometrical weight functions that are…

Soft Condensed Matter · Physics 2009-11-11 Ansgar Esztermann , Hendrik Reich , Matthias Schmidt

In this research. we analyze the potential of Feature Density (HD) as a way to comparatively estimate machine learning (ML) classifier performance prior to training. The goal of the study is to aid in solving the problem of…

Computation and Language · Computer Science 2022-06-07 Juuso Eronen , Michal Ptaszynski , Fumito Masui , Gniewosz Leliwa , Michal Wroczynski

An overview of several recent developments in density functional theory for classical inhomogeneous liquids is given. We show how Levy's constrained search method can be used to derive the variational principle that underlies density…

Soft Condensed Matter · Physics 2013-01-01 M. Schmidt , M. Burgis , W. S. B. Dwandaru , G. Leithall , P. Hopkins

We use machine learning methods on local structure to identify flow defects - or regions susceptible to rearrangement - in jammed and glassy systems. We apply this method successfully to two disparate systems: a two dimensional experimental…

The swift progression of machine learning (ML) has not gone unnoticed in the realm of statistical mechanics. ML techniques have attracted attention by the classical density-functional theory (DFT) community, as they enable discovery of…

Statistical Mechanics · Physics 2023-09-15 Antonio Malpica-Morales , Peter Yatsyshin , Miguel A. Duran-Olivencia , Serafim Kalliadasis

Density functional theory is used to study colloidal hard-rod fluids near an individual right-angled wedge or edge as well as near a hard wall which is periodically patterned with rectangular barriers. The Zwanzig model, in which the…

Soft Condensed Matter · Physics 2009-11-10 L. Harnau , F. Penna , S. Dietrich

Three dimensional implementations of liquid state theories offer an efficient alternative to computer simulations for the atomic-level description of aqueous solutions in complex environments. In this context, we present a (classical)…

Chemical Physics · Physics 2013-02-13 Guillaume Jeanmairet , Maximilien Levesque , Rodolphe Vuilleumier , Daniel Borgis

We prove that the lowest free energy of a classical interacting system at temperature $T$ with a prescribed density profile $\rho(x)$ can be approximated by the local free energy $\int f_T(\rho(x))dx$, provided that $\rho$ varies slowly…

Mathematical Physics · Physics 2024-08-28 Michal Jex , Mathieu Lewin , Peter Madsen
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