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A review of electronic dynamics of single-impurity and many-impurity Anderson models is contained in this report. Those models are used widely for many of the applications in diverse fields of interest, such as surface physics, theory of…

Strongly Correlated Electrons · Physics 2015-03-04 A. L. Kuzemsky

There is an opportunity for deep learning to revolutionize science and technology by revealing its findings in a human interpretable manner. To do this, we develop a novel data-driven approach for creating a human-machine partnership to…

Machine Learning · Computer Science 2022-03-23 Nicolas Boullé , Christopher J. Earls , Alex Townsend

In this work, we present a mesh-independent, data-driven library, chebgreen, to mathematically model one-dimensional systems, possessing an associated control parameter, and whose governing partial differential equation is unknown. The…

Machine Learning · Computer Science 2025-09-03 Harshwardhan Praveen , Jacob Brown , Christopher Earls

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

Discovering hidden partial differential equations (PDEs) and operators from data is an important topic at the frontier between machine learning and numerical analysis. This doctoral thesis introduces theoretical results and deep learning…

Numerical Analysis · Mathematics 2022-10-31 Nicolas Boullé

Green's function provides an inherent connection between theoretical analysis and numerical methods for elliptic partial differential equations, and general absence of its closed-form expression necessitates surrogate modeling to guide the…

Numerical Analysis · Mathematics 2025-09-16 Qi Sun , Shengyan Li , Bowen Zheng , Lili Ju , Xuejun Xu

Neural operators are a popular technique in scientific machine learning to learn a mathematical model of the behavior of unknown physical systems from data. Neural operators are especially useful to learn solution operators associated with…

Numerical Analysis · Mathematics 2022-08-05 Nicolas Boullé , Seick Kim , Tianyi Shi , Alex Townsend

The Green's function method has applications in several fields in Physics, from classical differential equations to quantum many-body problems. In the quantum context, Green's functions are correlation functions, from which it is possible…

Mesoscale and Nanoscale Physics · Physics 2016-10-14 Mariana M. Odashima , Beatriz G. Prado , E. Vernek

In this work we perform a Green's function analysis of giant-dipole systems. First we derive the Green's functions of different magnetically field-dressed systems, in particular of electronically highly excited atomic species in crossed…

Atomic Physics · Physics 2018-01-17 Thomas Stielow , Stefan Scheel , Markus Kurz

Green's function plays a significant role in both theoretical analysis and numerical computing of partial differential equations (PDEs). However, in most cases, Green's function is difficult to compute. The troubles arise in the following…

Machine Learning · Computer Science 2022-04-29 Guochang Lin , Fukai Chen , Pipi Hu , Xiang Chen , Junqing Chen , Jun Wang , Zuoqiang Shi

Simulating the dynamics of a nonequilibrium quantum many-body system by computing the two-time Green's function associated with such a system is computationally challenging. However, we are often interested in the time diagonal of such a…

Statistical Mechanics · Physics 2021-07-21 Jia Yin , Yang-hao Chan , Felipe da Jornada , Diana Qiu , Chao Yang , Steven G. Louie

In this paper we develop a way of obtaining Green's functions for partial differential equations with linear involutions by reducing the equation to a higher-order PDE without involutions. The developed theory is applied to a model of heat…

Classical Analysis and ODEs · Mathematics 2017-07-05 F. Adrián F. Tojo , Pedro J. Torres

Traditional numerical methods, such as the finite element method and finite volume method, adress partial differential equations (PDEs) by discretizing them into algebraic equations and solving these iteratively. However, this process is…

Computational Physics · Physics 2025-07-22 Jianghang Gu , Ling Wen , Yuntian Chen , Shiyi Chen

An end-to-end strategy for hybrid quantum-classical computations of Green's functions in many-body systems is presented and applied to the pairing model. The scheme makes explicit use of the spectral representation of the Green's function,…

Nuclear Theory · Physics 2026-05-01 Samuel Aychet-Claisse , Denis Lacroix , Vittorio Somà , Jing Zhang

We present an overview of electronic device modeling using non-equilibrium Green function techniques. The basic approach developed in the early 1970s has become increasingly popular during the last 10 years. The rise in popularity was…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Roger K. Lake , Rajeev R. Pandey

Green's functions characterize the fundamental solutions of partial differential equations; they are essential for tasks ranging from shape analysis to physical simulation, yet they remain computationally prohibitive to evaluate on…

Graphics · Computer Science 2026-02-16 Joao Teixeira , Eitan Grinspun , Otman Benchekroun

The basic mathematical properties of Green's functions used in statistical mechanics as well as the equations defining these functions and the techniques of solving these equations are reviewed. An approach is presented called the…

Statistical Mechanics · Physics 2007-05-23 V. I. Yukalov

Several widely used methods for the calculation of band structures and photo emission spectra, such as the GW approximation, rely on Many-Body Perturbation Theory. They can be obtained by iterating a set of functional differential equations…

Strongly Correlated Electrons · Physics 2012-01-31 Giovanna Lani , Pina Romaniello , Lucia Reining

In this letter, an approach to accelerate the matrix filling in method of moment (MOM) is presented. Based on the fact that the Green function is dependent on the Euclidean distance between the source and the observation points, we…

Numerical Analysis · Mathematics 2024-12-20 Shunchuan Yang , Donglin Su

During the past three decades, the advantageous concept of the Green's function has been extended from linear systems to nonlinear ones. At that, there exist a rigorous and an approximate extensions. The rigorous extension introduces the…

Mathematical Physics · Physics 2018-03-28 Asatur Khurshudyan
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