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Predictivity of the Kohn-Sham approach to dynamical problems, when regarded as an initial value problem in a time-dependent density functional framework, is analysed for a class of models for which the argument devised in the work of Maitra…

Other Condensed Matter · Physics 2015-06-16 Walter Tarantino

A general condition determining the optimal performance of a complex system has not yet been found and the possibility of its existence is unknown. To contribute in this direction, an optimization algorithm as a complex system is presented.…

Computational Complexity · Computer Science 2007-05-23 Victor Korotkikh , Galina Korotkikh , Darryl Bond

Optimization problems with composite functions consist of an objective function which is the sum of a smooth and a (convex) nonsmooth term. This particular structure is exploited by the class of proximal gradient methods and some of their…

Optimization and Control · Mathematics 2022-10-17 Christian Kanzow , Theresa Lechner

The Hohenberg-Kohn theorem and the Kohn-Sham equations, which are at the basis of the Density Functional Theory, are reformulated in terms of a particular many-body density, which is translational invariant and therefore is relevant for…

Nuclear Theory · Physics 2021-09-29 A. Kievsky , G. Orlandini , M. Gattobigio

One of the potential applications of a quantum computer is solving quantum chemical systems. It is known that one of the fastest ways to obtain somewhat accurate solutions classically is to use approximations of density functional theory.…

Quantum Physics · Physics 2020-11-18 Thomas E. Baker , David Poulin

Chemical accuracy serves as an important metric for assessing the effectiveness of the numerical method in Kohn--Sham density functional theory. It is found that to achieve chemical accuracy, not only the Kohn--Sham wavefunctions but also…

Computational Physics · Physics 2023-10-25 Yang Kuang , Yedan Shen , Guanghui Hu

The gas of the interacted electrons is usually described within Kohn-Sham approximation by the set of Poisson and Schr\"{o}dinger equations with an effective potential for the single-particle wave functions. The solution of these equations…

Materials Science · Physics 2007-05-23 A. Ya. Shul'man , D. V. Posvyanskii

We advocate an optimization procedure for variable density sampling in the context of compressed sensing. In this perspective, we introduce a minimization problem for the coherence between the sparsity and sensing bases, whose solution…

Information Theory · Computer Science 2011-09-29 Gilles Puy , Pierre Vandergheynst , Yves Wiaux

It is well known that effective potentials can be gauge-dependent while their values at extrema should be gauge-invariant. Unfortunately, establishing this invariance in perturbation theory is not straightforward, since contributions from…

High Energy Physics - Phenomenology · Physics 2015-06-22 Anders Andreassen , William Frost , Matthew D. Schwartz

We introduce a novel approach for decomposing and learning every scale of a given multiscale objective function in $\mathbb{R}^d$, where $d\ge 1$. This approach leverages a recently demonstrated implicit bias of the optimization method of…

Numerical Analysis · Mathematics 2024-01-09 Xingjie Helen Li , Molei Tao

We have derived a new method which allows to compute the full and the Pauli reference kinetic potentials for atoms and molecules in a real space representation. This is done by applying the optimized effective potential (OEP) method to…

Chemical Physics · Physics 2020-05-08 Szymon Śmiga , Sylwia Siecińska , Eduardo Fabiano

Optimal maps, solutions to the optimal transportation problems, are completely determined by the corresponding c-convex potential functions. In this paper, we give simple sufficient conditions for a smooth function to be c-convex when the…

Differential Geometry · Mathematics 2010-06-22 Paul W. Y. Lee

The optimized-effective-potential (OEP) method is a special technique to construct local Kohn-Sham potentials from general orbital-dependent energy functionals. In a recent publication [M. Betzinger, C. Friedrich, S. Bl\"ugel, A. G\"orling,…

Materials Science · Physics 2012-06-22 Markus Betzinger , Christoph Friedrich , Andreas Görling , Stefan Blügel

Optimization-based (OB) alternatives to traditional flux limiters couch preservation of properties such as local bounds and maximum principles into optimization problems, which impose these properties through inequality constraints. In this…

Optimization and Control · Mathematics 2024-12-30 Falko Ruppenthal , Denis Ridzal , Dmitri Kuzmin , Pavel Bochev

A new exact projective penalty method is proposed for the equivalent reduction of constrained optimization problems to nonsmooth unconstrained ones. In the method, the original objective function is extended to infeasible points by summing…

Optimization and Control · Mathematics 2023-12-05 Vladimir Norkin

The optimal transport problem with quadratic regularization is useful when sparse couplings are desired. The density of the optimal coupling is described by two functions called potentials; equivalently, potentials can be defined as a…

Optimization and Control · Mathematics 2025-03-11 Marcel Nutz

We present a novel way to compute the one-loop ring-improved effective potential numerically, which avoids the spurious appearence of complex expressions and at the same time is free from the renormalization ambiguities of the…

High Energy Physics - Theory · Physics 2015-06-26 G. Palma , L. Vergara

We present a new density-functional method of the self-consistent electronic-structure calculation which does not exploit any local density approximations (LDA). We use the exchange-correlation energy which consists of the exact exchange…

Statistical Mechanics · Physics 2009-10-30 Takao Kotani

We propose a way to improve energy density functionals (EDFs) in the density functional theory based on the combination of the inverse Kohn--Sham method and the density functional perturbation theory. Difference between the known EDF and…

Chemical Physics · Physics 2019-11-22 Tomoya Naito , Daisuke Ohashi , Haozhao Liang

Minimax optimization problems arises from both modern machine learning including generative adversarial networks, adversarial training and multi-agent reinforcement learning, as well as from tradition research areas such as saddle point…

Optimization and Control · Mathematics 2020-04-22 Yu-HOng Dai , Liwei Zhang
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