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Related papers: Low-Scaling algorithms for $GW$ and constrained ra…

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We develop a fast and scalable numerical approach to solve Wasserstein gradient flows (WGFs), particularly suitable for high-dimensional cases. Our approach is to use general reduced-order models, like deep neural networks, to parameterize…

Numerical Analysis · Mathematics 2024-05-24 Yijie Jin , Shu Liu , Hao Wu , Xiaojing Ye , Haomin Zhou

The General Spectral Modeling (GSM) code employs the quasi-static approximation, a standard, low-density methodology that assumes the ionization balance is separable from a determination of the excited-state populations that give rise to…

Atomic Physics · Physics 2008-11-26 Justin Oelgoetz , Christopher J. Fontes , Hong Lin Zhang , Anil K. Pradhan

In this paper a local approximation method on the sphere is presented. As interpolation scheme we consider a partition of unity method, such as the modified spherical Shepard's method, which uses zonal basis functions (ZBFs) plus spherical…

Numerical Analysis · Mathematics 2014-04-08 Alessandra De Rossi

Linear-scaling implementations of density functional theory (DFT) reach their intended efficiency regime only when applied to systems having a physical size larger than the range of their Kohn-Sham density matrix (DM). This causes a problem…

Chemical Physics · Physics 2022-03-25 Marcel David Fabian , Ben Shpiro , Eran Rabani , Daniel Neuhauser , Roi Baer

We introduce the discrete version of the Hutchinson--Barnsley theory providing algorithms to approximate the Hutchinson measure for iterated function systems (IFS) and generalized iterated function systems (GIFS) complementing the discrete…

Dynamical Systems · Mathematics 2020-07-15 Rudnei D. da Cunha , Elismar R. Oliveira , Filip Strobin

We introduce an alternative route to quasiparticle self-consistent $GW$ calculations ($\mathrm{qs}GW$) on the basis of a Joint Approximate Diagonalization of the one-body $GW$ Green's functions $G(\varepsilon_n^{QP})$ taken at the input…

Materials Science · Physics 2024-12-05 Ivan Duchemin , Xavier Blase

Implicit particle filtering is a sequential Monte Carlo method for data assim- ilation, designed to keep the number of particles manageable by focussing attention on regions of large probability. These regions are found by min- imizing, for…

Numerical Analysis · Mathematics 2015-05-30 Matthias Morzfeld , Alexandre J. Chorin

The electronic structure calculations remain a major bottleneck in ab initio nonadiabatic molecular dynamics. We develop an efficient TDDFT-based FSSH implementation in the GPU4PySCF package for medium-sized molecular systems. Our approach…

Chemical Physics · Physics 2026-05-08 Cheng Fan , Zhichen Pu , Zehao Zhou , Yuanheng Wang , Yi Qin Gao , Qiming Sun

We consider the problem of inference for nonlinear, multivariate diffusion processes, satisfying It\^o stochastic differential equations (SDEs), using data at discrete times that may be incomplete and subject to measurement error. Our…

Computation · Statistics 2021-09-27 Andrew Golightly , Chris Sherlock

We propose a parametric sampling strategy for the reduction of large-scale PDE systems with multidimensional input parametric spaces by leveraging models of different fidelity. The design of this methodology allows a user to adaptively…

Numerical Analysis · Mathematics 2023-01-24 Manisha Chetry , Domenico Borzacchiello , Lucas Lestandi , Luisa Rocha Da Silva

Pair atomic density fitting (PADF) is a promising strategy to reduce the scaling with system size of quantum chemical methods for the calculation of the correlation energy like the direct random phase approximation (RPA) or second-order…

Chemical Physics · Physics 2023-03-14 Edoardo Spadetto , Pier Herman Theodoor Philipsen , Arno Förster , Lucas Visscher

In the present work, we introduce a Self-Consistent Density-Functional Embedding technique, which leaves the realm of standard energy-functional approaches in Density Functional Theory and targets directly the density-to-potential mapping…

Computational Physics · Physics 2019-07-17 Uliana Mordovina , Teresa E. Reinhard , Iris Theophilou , Heiko Appel , Angel Rubio

Particle filtering methods can be applied to estimation problems in discrete spaces on bounded domains, to sample from and marginalise over unknown hidden states. As in continuous settings, problems such as particle degradation can arise:…

In this work, we develop an adaptive algorithm for the efficient numerical solution of the minimum compliance problem in topology optimization. The algorithm employs the phase field approximation and continuous density field. The adaptive…

Optimization and Control · Mathematics 2024-04-18 Bangti Jin , Jing Li , Yifeng Xu , Shengfeng Zhu

The particle-particle random phase approximation (pp-RPA) has been shown to be capable of describing double, Rydberg, and charge transfer excitations, for which the conventional time-dependent density functional theory (TDDFT) might not be…

Computational Physics · Physics 2017-04-26 Jianfeng Lu , Haizhao Yang

Radial basis function generated finite difference (RBF-FD) methods for PDEs require a set of interpolation points which conform to the computational domain $\Omega$. One of the requirements leading to approximation robustness is to place…

Numerical Analysis · Mathematics 2021-04-07 Igor Tominec , Eva Breznik

This paper presents and analyzes a parallelizable iterative procedure based on domain decomposition for primal-dual weak Galerkin (PDWG) finite element methods applied to the Poisson equation. The existence and uniqueness of the PDWG…

Numerical Analysis · Mathematics 2024-07-02 Chunmei Wang , Junping Wang

Over many years, computational simulations based on Density Functional Theory (DFT) have been used extensively to study many different materials at the atomic scale. However, its application is restricted by system size, leaving a number of…

Mesoscale and Nanoscale Physics · Physics 2018-12-05 Carlos Romero-Muñiz , Ayako Nakata , Pablo Pou , David R. Bowler , Tsuyoshi Miyazaki , Rubén Pérez

We present an extension to the iterative Boltzmann inversion method to generate coarse-grained models with three-body intramolecular potentials that can reproduce correlations in structural distribution functions. The coarse-grained…

Computational Physics · Physics 2023-11-27 Jianlan Ye , Vipin Agrawal , Minghao Liu , Jing Hu , Jay Oswald

In this work, we propose a novel low-complexity reduced-rank scheme and consider its application to linear interference suppression in direct-sequence ultra-wideband (DS-UWB) systems. Firstly, we investigate a generic reduced-rank scheme…

Information Theory · Computer Science 2013-05-16 Sheng Li , Rodrigo C. de Lamare