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The correlated density appears in many physical systems ranging from dense interacting gases up to Fermi liquids which develop a coherent state at low temperatures, the superconductivity. One consequence of the correlated density is the…

Superconductivity · Physics 2008-11-26 Klaus Morawetz , Pavel Lipavský , Jan Koláček , Ernst Helmut Brandt , Michael Schreiber

The derivation of linear response theory within polarizable embedding is carried out from a rigorous quantum-mechanical treatment of a composite system. Two different subsystem decompositions (symmetric and nonsymmetric) of the linear…

Chemical Physics · Physics 2017-10-09 Nanna Holmgaard List , Patrick Norman , Jacob Kongsted , Hans Jørgen Aagaard Jensen

Machine learning is a powerful tool to design accurate, highly non-local, exchange-correlation functionals for density functional theory. So far, most of those machine learned functionals are trained for systems with an integer number of…

With the development of low order scaling methods for performing Kohn-Sham Density Functional Theory, it is now possible to perform fully quantum mechanical calculations of systems containing tens of thousands of atoms. However, with an…

Chemical Physics · Physics 2020-04-03 William Dawson , Stephan Mohr , Laura E. Ratcliff , Takahito Nakajima , Luigi Genovese

We extend density matrix embedding theory to periodic systems, resulting in an electronic band structure method for solid-state materials. The electron correlation can be captured by means of a local impurity model using various choices of…

Strongly Correlated Electrons · Physics 2019-09-27 Hung Q. Pham , Matthew R. Hermes , Laura Gagliardi

In the framework of the Density Functional Theory for superconductors, we study the restoration of the particle number symmetry by means of the projection technique. Conceptual problems are outlined and numerical difficulties are discussed.…

Nuclear Theory · Physics 2008-12-18 J. Dobaczewski , M. V. Stoitsov , W. Nazarewicz , P. -G. Reinhard

Frozen Density Embedding (FDE) represents a versatile embedding scheme to describe the environmental effect on the electron dynamics in molecular systems. The extension of the general theory of FDE to the real-time time-dependent Kohn-Sham…

The isothermal compressibility of a general crystal is derived and discussed within (classical) density functional theory. Starting from the microscopic particle density, we carefully coarse grain to obtain the thermodynamic compressibility…

Soft Condensed Matter · Physics 2015-07-30 Christof Walz , Grzegorz Szamel , Matthias Fuchs

The problem of unstable particle decay is discussed to show how elementarity of a subsystem immersed in an infinitely larger environment is lost. The decay law, when the same kind of particles as decay product make up a thermal medium, is…

High Energy Physics - Phenomenology · Physics 2007-05-23 M. Yoshimura

Selected theoretical developments in modeling of deposition of submicrometer size (submicron) particles on solid surfaces, with and without surface diffusion, of interest in colloid, polymer, and certain biological systems, are surveyed. We…

Materials Science · Physics 2008-10-16 Vladimir Privman

Quantum--Mechanical methods that are both computationally fast and accurate are not yet available for electronic excitations having charge transfer character. In this work, we present a significant step forward towards this goal for those…

Chemical Physics · Physics 2015-06-12 Michele Pavanello , Troy Van Voorhis , Lucas Visscher , Johannes Neugebauer

We develop a method in which the electronic densities of small fragments determined by Kohn-Sham density functional theory (DFT) are embedded using stochastic DFT to form the exact density of the full system. The new method preserves the…

Chemical Physics · Physics 2015-06-19 Daniel Neuhauser , Roi Baer , Eran Rabani

We demonstrate the existence of different density-density functionals designed to retain selected properties of the many-body ground state in a non-interacting solution starting from the standard density functional theory ground state. We…

Other Condensed Matter · Physics 2009-11-13 F. A. Reboredo , P. R. C. Kent

Realistic nucleon-nucleon interaction induce correlations to the nuclear many-body system which lead to a fragmentation of the single-particle strength over a wide range of energies and momenta. We address the question of how this…

Nuclear Theory · Physics 2007-05-23 Arnau Rios , Artur Polls , Angels Ramos , Herbert Müther

We present a new variational model for computing the electronic first-order density matrix of a crystalline material in presence of a local defect. A natural way to obtain variational discretizations of this model is to expand the…

Other Condensed Matter · Physics 2009-11-13 Eric Cances , Amelie Deleurence , Mathieu Lewin

In this paper, we introduce and develop the circle embedding method. This method hinges essentially on a combinatorial-geometric structure which we choose to call circles of partition. We provide applications in the context of problems that…

General Mathematics · Mathematics 2026-04-21 Theophilus Agama , Berndt Gensel

A new method for the computation of conserved densities of nonlinear differential-difference equations is applied to Toda lattices and discretizations of the Korteweg-de Vries and nonlinear Schrodinger equations. The algorithm, which can be…

solv-int · Physics 2009-10-30 Unal Goktas , Willy Hereman , Grant Erdmann

Recently, we have proposed a new diffusive representation for fractional derivatives and, based on this representation, suggested an algorithm for their numerical computation. From the construction of the algorithm, it is immediately…

Numerical Analysis · Mathematics 2022-04-12 Kai Diethelm

Density matrix perturbation theory [Phys. Rev. Lett. Vol. 92, 193001 (2004)] provides an efficient framework for the linear scaling computation of response properties [Phys. Rev. Lett. Vol. 92, 193002 (2004)]. In this article, we generalize…

Computational Physics · Physics 2009-11-11 Anders M. N. Niklasson , Valery Weber , Matt Challacombe

Low-dimensional embedding, manifold learning, clustering, classification, and anomaly detection are among the most important problems in machine learning. The existing methods usually consider the case when each instance has a fixed,…

Machine Learning · Computer Science 2012-02-20 Barnabas Poczos , Liang Xiong , Jeff Schneider