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We present a method to considerably improve the numerical performance for solving Eliashberg-type coupled equations on the imaginary axis. Instead of the standard practice of introducing a hard numerical cutoff for treating the infinite…

Superconductivity · Physics 2019-05-22 Fabian Schrodi , Alex Aperis , Peter M. Oppeneer

We introduce an improved approach for obtaining smooth finite-temperature spectral functions of quantum impurity models using the numerical renormalization group (NRG) technique. It is based on calculating first the Green's function on the…

Strongly Correlated Electrons · Physics 2013-07-10 Žiga Osolin , Rok Žitko

We present an efficient implementation of a surface Green's-function method for atomistic modeling of surfaces within the framework of density functional theory using a pseudopotential localized basis set approach. In this method, the…

The many-body Green's function theory with the random-phase approximation is applied to the study of easy-plane spin-1/2 ferromagnets in an in-plane magnetic field. We demonstrate that the usual procedure, in which only the three Green's…

Strongly Correlated Electrons · Physics 2009-11-13 Daisuke Yamamoto , Synge Todo , Susumu Kurihara

The integral equation method is widely used in numerical simulations of 2D/3D acoustic and electromagnetic scattering problems, which needs a large number of values of the Green's functions. A significant topic is the scattering problems in…

Numerical Analysis · Mathematics 2018-07-26 Bo Zhang , Ruming Zhang

A stochastic method is described for estimating Green's functions (GF's), appropriate to linear advection-diffusion-reaction transport problems, evolving in arbitrary geometries. By allowing straightforward construction of approximate,…

We present an algorithm to compute Green's functions on quantum computers for interacting electron systems, which is a challenging task on conventional computers. It uses a continued fraction representation based on the Lanczos method,…

Quantum Physics · Physics 2022-12-07 Francois Jamet , Abhishek Agarwal , Ivan Rungger

Learning the Green's function using deep learning models enables to solve different classes of partial differential equations. A practical limitation of using deep learning for the Green's function is the repeated computationally expensive…

Machine Learning · Computer Science 2023-08-02 Kishan Wimalawarne , Taiji Suzuki , Sophie Langer

We present an extension of the AAA (adaptive Antoulas--Anderson) algorithm for periodic functions, called 'AAAtrig'. The algorithm uses the key steps of AAA approximation by (i) representing the approximant in (trigonometric) barycentric…

Numerical Analysis · Mathematics 2020-08-13 Peter J. Baddoo

A new fast multipole formulation for solving elliptic difference equations on unbounded domains and its parallel implementation are presented. These difference equations can arise directly in the description of physical systems, e.g.…

Computational Physics · Physics 2016-04-08 Sebastian Liska , Tim Colonius

We present and review an efficient method to calculate the retarded Green's function in multi-terminal nanostructures; which is needed in order to calculate the conductance through the system and the local particle densities within it. The…

Mesoscale and Nanoscale Physics · Physics 2015-06-16 G. Thorgilsson , G. Viktorsson , S. I. Erlingsson

This paper presents a novel method for transient stability analysis (TSA) that circumvents the limitations of sequential numerical integration and energy functions. The proposed method begins by constructing a trajectory-dependent stability…

Systems and Control · Electrical Eng. & Systems 2025-11-18 Wenhao Wu , Dan Wu , Bin Wang , Jiabing Hu

From perturbation theory, Green's functions are known for providing a simple and convenient access to the (complete) spectrum of atoms and ions. Having these functions available, they may help carry out perturbation expansions to any order…

Quantum Physics · Physics 2007-05-23 Peter Koval , Stephan Fritzsche

The Fast Multipole Method (FMM) obeys periodic boundary conditions "natively" if it uses a periodic Green function for computing the multipole expansion in the interaction zone of each FMM oct-tree node. One can define the "optimal" Green…

Computational Physics · Physics 2021-03-10 Nickolay Y. Gnedin

We consider the problem of finding a rational function in barycentric form to approximate a given function or data set in $\mathbb{R}$ or $\mathbb{C}$. The famous AAA algorithm, introduced in 2018, constructs such a rational function: the…

Numerical Analysis · Mathematics 2025-08-18 William Mitchell

We present a data-driven approach to mathematically model physical systems whose governing partial differential equations are unknown, by learning their associated Green's function. The subject systems are observed by collecting…

Numerical Analysis · Mathematics 2023-03-13 Harshwardhan Praveen , Nicolas Boulle , Christopher Earls

Matsubara dynamics has recently emerged as the most general form of a quantum-Boltzmann-conserving classical dynamics theory for the calculation of single-time correlation functions. Here, we present a generalization of Matsubara dynamics…

Chemical Physics · Physics 2019-09-04 Kenneth A. Jung , Pablo E. Videla , Victor S. Batista

We report an implementation of self-consistent Green's function many-body theory within a second-order approximation (GF2) for application with molecular systems. This is done by iterative solution of the Dyson equation expressed in matrix…

Chemical Physics · Physics 2016-11-15 Jordan J. Phillips , Dominika Zgid

Within the non-equilibrium Green's function technique on the real time contour, the Phi-functional method of Baym is reviewed and generalized to arbitrary non-equilibrium many-particle systems. The scheme may be closed at any desired order…

High Energy Physics - Phenomenology · Physics 2008-11-26 Yu. B. Ivanov , J. Knoll , D. N. Voskresensky

The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and…