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Boltzmann's principle is used to select the "most probable" realization (macrostate) of an isolated or closed thermodynamic system, containing a small number of particles ($N \llsp \infty$), for both classical and quantum statistics. The…

Statistical Mechanics · Physics 2015-05-13 Robert K. Niven

In this paper we consider inverse problems for resistor networks and for models obtained via the Finite Element Method (FEM) for the conductivity equation. These correspond to discrete versions of the inverse conductivity problem of…

Analysis of PDEs · Mathematics 2013-07-10 Matti Lassas , Mikko Salo , Leo Tzou

We analyze the equilibration process between two either fermionic or bosonic reservoirs containing ultracold atoms with a fixed total number of particles that are weakly connected via a few-level quantum system. We allow for both the…

Density functional theory is the workhorse of modern electronic structure calculations, with wide-ranging applications in chemistry, physics, materials science, and machine learning. At its heart lies the exchange-correlation functional, a…

Chemical Physics · Physics 2026-02-20 Fabien Tran , Susi Lehtola , Stefano Pittalis , Miguel A. L. Marques

We develop a semiclassical density functional theory in the context of quantum dots. Coulomb blockade conductance oscillations have been measured in several experiments using nanostructured quantum dots. The statistical properties of these…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Denis Ullmo , Tatsuro Nagano , Steven Tomsovic , Harold U. Baranger

This thesis describes several topics related to finite temperature studies of strongly correlated systems: finite temperature density matrix embedding theory (FT-DMET), finite temperature metal-insulator transition, and quantum algorithms…

Strongly Correlated Electrons · Physics 2023-03-01 Chong Sun

We reformulate the strong-interaction limit of electronic density functional theory in terms of a classical problem with a degenerate minimum. This allows us to clarify many aspects of this limit, and to write a general solution, which is…

Materials Science · Physics 2007-05-23 Michael Seidl , Paola Gori-Giorgi , Andreas Savin

The dielectric properties of molecules or nanostructures are usually modified in a complex manner, when assembled into a condensed phase. We propose a first-principles method to compute polarizabilities of sub-entities of solids and…

Chemical Physics · Physics 2018-09-10 Ding Pan , Marco Govoni , Giulia Galli

This paper analyses the finite element component of the error when using preintegration to approximate the cdf and pdf for uncertainty quantification (UQ) problems involving elliptic PDEs with random inputs. It is a follow up to Gilbert,…

Numerical Analysis · Mathematics 2025-10-28 Alexander D. Gilbert

An expansion method for perturbation of the zero temperature grand canonical density matrix is introduced. The method achieves quadratically convergent recursions that yield the response of the zero temperature density matrix upon variation…

Materials Science · Physics 2009-11-10 Anders M. N. Niklasson , Matt Challacombe

We introduce the notion of matrices graph, defining continued fraction algorithms where the past and the future are almost independent. We provide an algorithm to convert more general algorithms into matrices graphs. We present an algorithm…

Dynamical Systems · Mathematics 2023-11-17 Paul Mercat

The restoration of particle number within Energy Density Functional theory is analyzed. It is shown that the standard method based on configuration mixing leads to a functional of both the projected and non-projected densities. As an…

Nuclear Theory · Physics 2011-08-08 Guillaume Hupin , Denis Lacroix , Michael Bender

Given $iid$ observations from an unknown absolute continuous distribution defined on some domain $\Omega$, we propose a nonparametric method to learn a piecewise constant function to approximate the underlying probability density function.…

Machine Learning · Statistics 2018-03-13 Dangna Li , Kun Yang , Wing Hung Wong

We examine the inference of quantum density operators from incomplete information by means of the maximization of general non-additive entropic forms. Extended thermodynamic relations are given. When applied to a bipartite spin 1/2 system,…

Quantum Physics · Physics 2015-05-20 N. Canosa , R. Rossignoli

The fractional quantum Hall effect remains a captivating area in condensed matter physics, characterized by strongly correlated topological order, which manifests as fractionalized excitations and anyonic statistics. Numerical simulations,…

Strongly Correlated Electrons · Physics 2025-10-27 Yi Yang , Yayun Hu , Zi-Xiang Hu

We introduce real-time density matrix embedding theory (DMET), a dynamical quantum embedding theory for computing non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static DMET, real-time DMET…

Chemical Physics · Physics 2017-11-03 Joshua S. Kretchmer , Garnet Kin-Lic Chan

Systems of reaction-diffusion equations are commonly used in biological models of food chains. The populations and their complicated interactions present numerous challenges in theory and in numerical approximation. In particular,…

Numerical Analysis · Mathematics 2015-10-28 Matthew Beauregard , Joshua Padgett , Rana Parshad

Two (so-called left and right) variants of N-centered ensemble density-functional theory (DFT) [Senjean and Fromager, Phys. Rev. A 98, 022513 (2018)] are presented. Unlike the original formulation of the theory, these variants allow for the…

Strongly Correlated Electrons · Physics 2020-02-25 Bruno Senjean , Emmanuel Fromager

We introduce a semi-implicit Milstein approximation scheme for some class of non-colliding particle systems modeled by systems of stochastic differential equations with non-constant diffusion coefficients. We show that the scheme converges…

Probability · Mathematics 2019-08-13 Hoang-Long Ngo , Duc-Trong Luong

We develop a materials descriptor based on the electronic density of states and investigate the similarity of materials based on it. As an application example, we study the Computational 2D Materials Database that hosts thousands of…

Materials Science · Physics 2022-01-07 Martin Kuban , Santiago Rigamonti , Markus Scheidgen , Claudia Draxl