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Related papers: RPA calculations with Gaussian expansion method

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We review our calculation method, Gaussian expansion method (GEM), and its applications to various few-body (3- to 5-body) systems such as 1) few-nucleon systems, 2) few-body structure of hypernuclei, 3) clustering structure of light nuclei…

Nuclear Theory · Physics 2018-09-14 Emiko Hiyama , Masayasu Kamimura

The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of…

Materials Science · Physics 2017-07-26 Xinguo Ren , Patrick Rinke , Christian Joas , Matthias Scheffler

The random phase approximation (RPA) has received a considerable interest in the field of modeling systems where noncovalent interactions are important. Its advantages over widely used density functional theory (DFT) approximations are the…

Chemical Physics · Physics 2019-12-04 Marcin Modrzejewski , Sirous Yourdkhani , Jiri Klimes

Relativistic Continuum Random Phase Approximation (CRPA) is used to investigate collective excitation phenomena in several spherical nuclei along the periodic table. We start from relativistic mean field calculations based on a covariant…

Nuclear Theory · Physics 2011-03-21 J. Daoutidis , P. Ring

The matrix equations of the random-phase approximation (RPA) are derived for the point-coupling Lagrangian of the relativistic mean-field (RMF) model. Fully consistent RMF plus (quasiparticle) RPA illustrative calculations of the isoscalar…

Nuclear Theory · Physics 2009-11-11 T. Niksic , D. Vretenar , P. Ring

We extensively develop a method of implementing mean-field calculations for deformed nuclei, using the Gaussian expansion method (GEM). This GEM algorithm has the following advantages: (i) it can efficiently describe the energy-dependent…

Nuclear Theory · Physics 2008-11-26 H. Nakada

We investigate the structure of ground-state heavy mesons within the light-front quark model, utilizing wave functions derived from the Single Gaussian Ansatz (SGA) and the Gaussian Expansion Method (GEM). By performing a $\chi^2$ fit to…

High Energy Physics - Phenomenology · Physics 2024-06-24 Ahmad Jafar Arifi , Lucas Happ , Shuhei Ohno , Makoto Oka

Using the adiabatic connection, we formulate the free energy in terms of the correlation function of a fictitious system, $h_{\lambda}({\bf r},{\bf r}')$, where $\lambda$ determines the interaction strength. To obtain $h_{\lambda}({\bf…

Statistical Mechanics · Physics 2016-06-15 Derek Frydel , Manman Ma

The random phase approximation (RPA) is attracting renewed interest as a universal and accurate method for first-principles total energy calculations. The RPA naturally accounts for long-range dispersive forces without compromising accuracy…

Materials Science · Physics 2013-03-04 Thomas Olsen , Kristian S. Thygesen

The matrix equations of the relativistic random-phase approximation (RRPA) are derived for an effective Lagrangian characterized by density-dependent meson-nucleon vertex functions. The explicit density dependence of the meson-nucleon…

Nuclear Theory · Physics 2009-11-07 T. Niksic , D. Vretenar , P. Ring

Self-consistent relativistic random-phase approximation (RPA) in the radial coordinate representation is established by using the finite amplitude method (FAM). Taking the isoscalar giant monopole resonance in spherical nuclei as example,…

Nuclear Theory · Physics 2013-10-16 Haozhao Liang , Takashi Nakatsukasa , Zhongming Niu , Jie Meng

In this thesis are shown developments in the random phase approximation (RPA) in the context of range-separated theories. We present advances in the formalism of the RPA in general, and particularly in the "dielectric matrix" formulation of…

Chemical Physics · Physics 2015-11-24 B. Mussard

A fast method is developed for calculating the Random-Phase-Approximation (RPA) correlation energy for density functional theory. The correlation energy is given by a trace over a projected RPA response matrix and the trace is taken by a…

Chemical Physics · Physics 2013-01-01 Daniel Neuhauser , Eran Rabani , Roi Baer

The random phase approximation (RPA) for the correlation energy functional of density functional theory has recently attracted renewed interest. Formulated in terms of the Kohn-Sham (KS) orbitals and eigenvalues, it promises to resolve some…

Other Condensed Matter · Physics 2009-11-13 Hong Jiang , Eberhard Engel

The Random Phase Approximation (RPA) and its variations and extensions are, without any doubt, the most widely used tools to describe Giant Resonances within a microscopic theory. In this chapter, we will start by discussing how RPA comes…

Nuclear Theory · Physics 2022-01-13 Gianluca Colo'

We present a family of \textit{Gaussian Mixture Approximation} (GMA) samplers for sampling unnormalised target densities, encompassing \textit{weights-only GMA} (W-GMA), \textit{Laplace Mixture Approximation} (LMA),…

Machine Learning · Computer Science 2025-10-01 Yongchao Huang

Random Phase Approximation (RPA) is the theory most commonly used to describe the excitations of many-body systems. In this article, the secular equations of the theory are obtained by using three different approaches: the equation of…

Nuclear Theory · Physics 2023-03-14 Giampaolo Co'

The random-phase approximation to the ground state correlation energy (RPA) in combination with exact exchange (EX) has brought Kohn-Sham (KS) density functional theory one step closer towards a universal, "general purpose first principles…

The status of different extensions of the Random Phase Approximation (RPA) is reviewed. The general framework is given within the Equation of Motion Method and the equivalent Green's function approach for the so-called Self-Consistent RPA…

Nuclear Theory · Physics 2021-08-25 P. Schuck , D. S. Delion , J. Dukelsky , M. Jemai , E. Litvinova , G. Roepke , M. Tohyama

Gaussian processes (GPs) are flexible distributions over functions that enable high-level assumptions about unknown functions to be encoded in a parsimonious, flexible and general way. Although elegant, the application of GPs is limited by…

Machine Learning · Statistics 2017-10-06 Thang D. Bui , Josiah Yan , Richard E. Turner
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