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Related papers: RPA calculations with Gaussian expansion method

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We develop and test efficient approximations to estimate ground state correlations associated with low- and zero-energy modes. The scheme is an extension of the generator-coordinate-method (GCM) within Gaussian overlap approximation (GOA).…

Nuclear Theory · Physics 2009-11-07 K. Hagino , P. -G. Reinhard , G. F. Bertsch

The random phase approximation (RPA) is exact for the exchange energy of a many-electron ground state, but RPA makes the correlation energy too negative by about 0.5 eV/electron. That large short-range error, which tends to cancel out of…

Computational Physics · Physics 2020-06-24 Tim Gould , Adrienn Ruzsinszky , John P. Perdew

Using Green-function many-body theory, we present the details of a formally exact adiabatic-connection fluctuation-dissipation density-functional theory based on range separation, which was sketched in Toulouse, Gerber, Jansen, Savin and…

Chemical Physics · Physics 2010-09-13 Julien Toulouse , Wuming Zhu , Janos G. Angyan , Andreas Savin

The calculation of minimum energy paths for transitions such as atomic and/or spin re-arrangements is an important task in many contexts and can often be used to determine the mechanism and rate of transitions. An important challenge is to…

Chemical Physics · Physics 2017-03-31 Olli-Pekka Koistinen , Emile Maras , Aki Vehtari , Hannes Jónsson

An application of a self-consistent version of RPA to quantum field theory with broken symmetry is presented. Although our approach can be applied to any bosonic field theory, we specifically study the $\phi^4$ theory in 1+1 dimensions. We…

High Energy Physics - Phenomenology · Physics 2007-05-23 H. Hansen , G. Chanfray , D. Davesne , P. Schuck

Generalized additive models (GAMs) provide a way to blend parametric and non-parametric (function approximation) techniques together, making them flexible tools suitable for many modeling problems. For instance, GAMs can be used to…

Methodology · Statistics 2023-03-07 Antti Solonen , Stratos Staboulis

We analyze, both analytically and numerically, the time-dependence of the return probability in closed systems of interacting particles. Main attention is paid to the interplay between two regimes, one of which is characterized by the…

Disordered Systems and Neural Networks · Physics 2009-11-11 F. M. Izrailev , A. Castaneda-Mendoza

The optimized effective potential (OEP) method presents an unambiguous way to construct the Kohn-Sham potential corresponding to a given diagrammatic approximation for the exchange-correlation functional. The OEP from the random-phase…

Materials Science · Physics 2023-07-18 Stefan Riemelmoser , Merzuk Kaltak , Georg Kresse

The self-consistent random phase approximation (RPA) based on a correlated realistic nucleon-nucleon interaction is used to evaluate correlation energies in closed-shell nuclei beyond the Hartree-Fock level. The relevance of contributions…

Nuclear Theory · Physics 2007-05-23 C. Barbieri , N. Paar , R. Roth , P. Papakonstantinou

We present a new method to obtain interaction part of a model Hamiltonian from the result of the first-principles calculation. The effective interaction contained in the model is determined based on the random phase approximation (RPA). In…

Materials Science · Physics 2017-04-26 Hirofumi Sakakibara , Seung Woo Jang , Hiori Kino , Myung Joon Han , Kazuhiko Kuroki , Takao Kotani

We present an approximation scheme for the calculation of the principal excitation energies and transition moments of finite many-body systems. The scheme is derived from a first order approximation to the self energy of a recently proposed…

Chemical Physics · Physics 2009-10-30 Joachim Brand , Lorenz S. Cederbaum

The Expectation-Maximization (EM) algorithm is a widely used method for maximum likelihood estimation in models with latent variables. For estimating mixtures of Gaussians, its iteration can be viewed as a soft version of the k-means…

Machine Learning · Statistics 2017-06-06 Constantinos Daskalakis , Christos Tzamos , Manolis Zampetakis

We develop a general approach to Stein's method for approximating a random process in the path space $D([0,T]\to R^d)$ by a real continuous Gaussian process. We then use the approach in the context of processes that have a representation as…

Probability · Mathematics 2024-01-24 A. D. Barbour , Nathan Ross , Guangqu Zheng

Gaussian Process (GP) emulators are widely used to approximate complex computer model behaviour across the input space. Motivated by the problem of coupling computer models, recently progress has been made in the theory of the analysis of…

Applications · Statistics 2022-04-20 Victoria Volodina , Nikki Sonenberg , Peter Challenor , Jim Q. Smith

In a recently developed approximation technique for quantum field theory the standard one-loop result is used as a seed for a recursive formula that gives a sequence of improved Gaussian approximations for the generating functional. In this…

High Energy Physics - Theory · Physics 2011-08-09 Antun Balaz , Aleksandar Belic , Aleksandar Bogojevic

A self-consistent random phase approximation (RPA) is proposed as an effective Hamiltonian method in Light-Front Field Theory (LFFT). We apply the general idea to the light-front massive Schwinger model to obtain a new bound state equation…

High Energy Physics - Theory · Physics 2009-10-31 Koji Harada

Covariant density functional theory, in the framework of self-consistent Relativistic Mean Field (RMF) and Relativistic Random Phase approximation (RPA), is for the first time applied to axially deformed nuclei. The fully self-consistent…

Nuclear Theory · Physics 2009-09-15 D. Pena Arteaga , P. Ring

Key to being able to accurately model the properties of realistic materials is being able to predict their properties in the thermodynamic limit. Nevertheless, because most many-body electronic structure methods scale as a high-order…

Chemical Physics · Physics 2024-04-04 Edgar Josué Landinez Borda , Kenneth O. Berard , Annette Lopez , Brenda Rubenstein

We present an efficient implementation of the random phase approximation (RPA) for molecular systems within the domain-based local pair natural orbital (DLPNO) framework. With optimized parameters, DLPNO-RPA achieves approximately 99.9%…

Chemical Physics · Physics 2025-08-18 Yu Hsuan Liang , Xing Zhang , Garnet Kin-Lic Chan , Timothy C. Berkelbach , Hong-Zhou Ye

We reconsider a nonparametric density model based on Gaussian processes. By augmenting the model with latent P\'olya--Gamma random variables and a latent marked Poisson process we obtain a new likelihood which is conjugate to the model's…

Machine Learning · Statistics 2018-05-30 Christian Donner , Manfred Opper
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