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The solution of complex many-body lattice models can often be found by defining an energy functional of the relevant density of the problem. For instance, in the case of the Hubbard model the spin-resolved site occupation is enough to…

Strongly Correlated Electrons · Physics 2019-02-20 James Nelson , Rajarshi Tiwari , Stefano Sanvito

The Hubbard model provides a test bed to investigate the complex behaviour arising from electron-electron interaction in strongly-correlated systems and naturally emerges as the foundation model for lattice density functional theory (DFT).…

Strongly Correlated Electrons · Physics 2025-01-29 Eoghan Cronin , Rajarshi Tiwari , Stefano Sanvito

Understanding the thermodynamic properties of many-body quantum systems and their emergence from microscopic laws is a topic of great significance due to its profound fundamental implications and extensive practical applications. Recent…

Quantum Physics · Physics 2024-09-05 Antonio Palamara , Francesco Plastina , Antonello Sindona , Irene D'Amico

The thermodynamics of the inhomogeneous one-dimensional repulsive fermionic Hubbard model with parabolic confinement is studied by a density-functional theory approach, based on Mermin's generalization to finite temperatures. A…

Strongly Correlated Electrons · Physics 2019-04-25 V. L. Campo

The formally exact framework of equilibrium Density Functional Theory (DFT) is capable of simultaneously and consistently describing thermodynamic and structural properties of interacting many-body systems in arbitrary external potentials.…

We prove by means of a renormalization group method that in weakly interacting many-electron systems at half-filling on a periodic hyper-cubic lattice, the free energy density uniformly converges to an analytic function of the coupling…

Mathematical Physics · Physics 2016-12-19 Yohei Kashima

We develop a thermodynamic theory for machine learning (ML) systems. Similar to physical thermodynamic systems which are characterized by energy and entropy, ML systems possess these characteristics as well. This comparison inspire us to…

Machine Learning · Computer Science 2024-04-23 Dong Zhang

We present a numerical modeling workflow based on machine learning (ML) which reproduces the the total energies produced by Kohn-Sham density functional theory (DFT) at finite electronic temperature to within chemical accuracy at negligible…

In this work, the zero-temperature limit of the thermodynamic spin-density functional theory is investigated. The coarse-grained approach to the equilibrium density operator is used to describe the equilibrium state. The characteristic…

Chemical Physics · Physics 2013-10-28 Robert Balawender

The formalism developed in the first paper of the series [arXiv:0901.1060] is applied to two thermodynamic systems: (i) of three global observables (the energy, the total electron number and the spin number), (ii) of one global observable…

Chemical Physics · Physics 2013-10-28 Robert Balawender , Andrzej Holas

We employ the numerical linked-cluster expansion to study finite-temperature properties of the uniform cubic lattice Hubbard model in the thermodynamic limit for a wide range of interaction strengths and densities. We carry out the…

Strongly Correlated Electrons · Physics 2016-09-13 Ehsan Khatami

In this chapter, we discuss recent advances and new opportunities through methods of machine learning for the field of classical density functional theory, dealing with the equilibrium properties of thermal nano- and micro-particle systems…

Statistical Mechanics · Physics 2024-06-12 Alessandro Simon , Martin Oettel

An approximate partition functional is derived for the infinite-dimensional Hubbard model. This functional naturally includes the exact solution of the Falicov-Kimball model as a special case, and is exact in the uncorrelated and atomic…

Condensed Matter · Physics 2009-10-22 Y. M. Li , N. d'Ambrumenil

We present a scheme for investigating arbitrary thermal observables in spatially inhomogeneous equilibrium many-body systems. Extending the grand canonical ensemble yields any given observable as an explicit hyper-density functional.…

Soft Condensed Matter · Physics 2024-09-10 Florian Sammüller , Silas Robitschko , Sophie Hermann , Matthias Schmidt

Finite temperature density functional theory requires representations for the internal energy, entropy, and free energy as functionals of the local density field. A central formal difficulty for an orbital-free representation is…

Statistical Mechanics · Physics 2011-05-12 James W. Dufty , S. B. Trickey

We revisit the machine-learning (ML) approach to the universal density functional $F[\mathbf{n}]$ of the one-dimensional Hubbard model with a site-dependent random potential $\mathbf{v}=\{v_{i}\}$. We generate exact ground-state data via…

Disordered Systems and Neural Networks · Physics 2026-03-03 Octavio D. R. Salmon , Minos A. Neto , J. Roberto Viana , Griffith Mendonça

The derivative discontinuity of the exchange-correlation (xc) energy at integer particle number is a property of the exact, unknown xc functional of density functional theory (DFT) which is absent in many popular local and semilocal…

Strongly Correlated Electrons · Physics 2015-06-11 Gao Xianlong , A-Hai Chen , I. V. Tokatly , S. Kurth

The resource theory of thermal operations, an established model for small-scale thermodynamics, provides an extension of equilibrium thermodynamics to nonequilibrium situations. On a lattice of any dimension with any translation-invariant…

Exotic phases of matter can emerge from strong correlations in quantum many-body systems. Quantum gas microscopy affords the opportunity to study these correlations with unprecedented detail. Here we report site-resolved observations of…

We describe a formulation of the density matrix embedding theory at finite temperature. We present a generalization of the ground-state bath orbital construction that embeds a mean-field finite-temperature density matrix up to a given order…

Strongly Correlated Electrons · Physics 2020-03-04 Chong Sun , Ushnish Ray , Zhi-Hao Cui , Miles Stoudenmire , Michel Ferrero , Garnet Kin-Lic Chan
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