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In non-classical linear transport the chord length distribution between collisions is non-exponential and attenuation does not respect Beer's law. Generalized radiative transfer (GRT) extends the classical theory to account for such…

Statistical Mechanics · Physics 2020-02-19 Eugene d'Eon

Multiple scattering methods are widely used to reduce the computational complexity of acoustic or electromagnetic scattering problems when waves propagate through media containing many identical inclusions. Historically, this numerical…

Numerical Analysis · Mathematics 2024-08-07 Carlos Borges , Leslie Greengard , Michael O'Neil , Manas Rachh

Green's function of the problem describing steady forward motion of bodies in an open ocean in the framework of the linear surface wave theory (the function is often referred to as Kelvin's wave source potential) is considered. Methods for…

Numerical Analysis · Mathematics 2014-11-04 Oleg V. Motygin

We show how to use the input-output formalism compute the propagator for an open quantum system, i.e. quantum networks with a low dimensional quantum system coupled to one or more loss channels. The total propagator is expressed entirely in…

Quantum Physics · Physics 2018-11-02 Rahul Trivedi , Kevin Fischer , Shanshan Xu , Shanhui Fan , Jelena Vuckovic

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

This introduction to Green's functions is based on their role as kernels of differential equations. The procedures to construct solutions to a differential equation with an external source or with an inhomogeneity term are put together to…

Mesoscale and Nanoscale Physics · Physics 2008-02-22 Ursula Schröter

This paper concerns diffraction-tomographic reconstruction of an object characterized by its scattering potential. We establish a rigorous generalization of the Fourier diffraction theorem in arbitrary dimension, giving a precise relation…

Numerical Analysis · Mathematics 2026-03-30 Clemens Kirisits , Michael Quellmalz , Eric Setterqvist

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

In this paper, dyadic Green's function for a graphene-dielectric stack is formulated based on the scattering superposition method. To this end, scattering Green's function in each layer is expanded in terms of cylindrical vector wave…

Computational Physics · Physics 2021-08-04 Shiva Hayati Raad , Zahra Atlasbaf , Mauro Cuevas

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

We propose a new procedure by using the recursive Green's functions which remove all the repetition terms from the time-independent perturbation series for finite-level quantum systems. These Green's functions are introduced as a…

Quantum Physics · Physics 2019-04-02 K. Ishida

We study the nonlinear elastic quantum electronic transport properties of nanoscopic devices using the Nonequilibrium Green's function (NEGF) method. The Green's function method allows us to expand the $I-V$ characteristics of a given…

Mesoscale and Nanoscale Physics · Physics 2009-07-14 Alexis R. Hernández , Caio H. Lewenkopf

We propose a first-principles method of efficiently evaluating electron-transport properties of very long systems. Implementing the recursive Green's function method and the shifted conjugate gradient method in the transport simulator based…

Mesoscale and Nanoscale Physics · Physics 2021-01-20 Yoshiyuki Egami , Shigeru Tsukamoto , Tomoya Ono

We derive a method to efficiently compute the Green function of on arbitrary Hamiltonians defined on semi-infinite and periodic quasi-one-dimensional lattices. Computing the Green function is the backbone of quantum transport, electronic…

Mesoscale and Nanoscale Physics · Physics 2021-05-18 Pablo San-Jose

Experimental advances allow for the inclusion of multiple probes to measure the transport properties of a sample surface. We develop a theory of dual-probe scanning tunnelling microscopy using a Green's Function formalism, and apply it to…

Mesoscale and Nanoscale Physics · Physics 2015-01-27 Mikkel Settnes , Stephen R. Power , Dirch H. Petersen , Antti-Pekka Jauho

The non-equilibrium Green's function (NEGF) approach offers a practical framework for simulating various phenomena in mesoscopic systems. As the dimension of electronic devices shrinks to just a few nanometers, the need for new…

Mesoscale and Nanoscale Physics · Physics 2025-04-09 Vahid Mosallanejad , Kuei-Lin Chiu , Wenjie Dou

The single-particle Green's function of an interacting Fermi system with dominant forward scattering is calculated by decoupling the interaction by means of a Hubbard-Stratonowich transformation involving a bosonic auxiliary field…

Condensed Matter · Physics 2007-05-23 Peter Kopietz

In this work, we propose an efficient computational scheme for first-principle quantum transport simulations to evaluate the open-boundary conditions. Its partitioning differentiates from conventional methods in that the contact self-energy…

Materials Science · Physics 2021-01-01 Guido Gandus , Youseung Lee , Daniele Passerone , Mathieu Luisier

Dyadic Green's function is an important tool of computational photonics, giving deeper insights into light-matter interaction. We present an operator approach to the derivation of the dyadic Green's function of a generic anisotropic…

Optics · Physics 2026-05-13 Aliaksandr Arlouski , Lei Gao , Dongliang Gao , Andrey Novitsky

Neural operators offer powerful approaches for solving parametric partial differential equations, but extending them to spherical domains remains challenging due to the need to preserve intrinsic geometry while avoiding distortions that…

Machine Learning · Computer Science 2026-04-10 Hao Tang , Hao Chen , Chao Li