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DFT calculations yield useful ground-state energies and densities, while Green's function techniques (such as $GW$) are mostly used to produce spectral functions. From the Galitskii-Migdal formula, we extract the exchange-correlation of DFT…

Chemical Physics · Physics 2024-03-13 Steven Crisostomo , E. K. U. Gross , Kieron Burke

A brief review of the SIESTA project is presented in the context of linear-scaling density-functional methods for electronic-structure calculations and molecular-dynamics simulations of systems with a large number of atoms. Applications of…

Materials Science · Physics 2015-06-25 Emilio Artacho , Daniel Sanchez-Portal , Pablo Ordejon , Alberto Garcia , Jose M. Soler

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

We describe a set of techniques for performing large scale ab initio calculations using multigrid accelerations and a real-space grid as a basis. The multigrid methods provide effective convergence acceleration and preconditioning on all…

mtrl-th · Physics 2008-02-03 E. L. Briggs , D. J. Sullivan , J. Bernholc

In this article we derive the lattice Green Functions (GFs) of graphene using a Tight Binding Hamiltonian incorporating both first and second nearest neighbour hoppings and allowing for a non-orthogonal electron wavefunction overlap. It is…

Mesoscale and Nanoscale Physics · Physics 2015-06-23 James A. Lawlor , Mauro S. Ferreira

We propose a fast and versatile algorithm to calculate local and transport properties such as conductance, shot noise, local density of state or local currents in mesoscopic quantum systems. Within the non equilibrium Green function…

Mesoscale and Nanoscale Physics · Physics 2008-03-18 Kyryl Kazymyrenko , Xavier Waintal

A numerical explicit method to evaluates transient solutions of linear partial differential non-homogeneous equation with constant coefficients is proposed.

Numerical Analysis · Computer Science 2010-11-11 Hiroshi Abe

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution times for complex problems. In this…

We present an approach to solid-state electronic-structure calculations based on the finite-element method. In this method, the basis functions are strictly local, piecewise polynomials. Because the basis is composed of polynomials, the…

Condensed Matter · Physics 2009-10-31 J. E. Pask , B. M. Klein , C. Y. Fong , P. A. Sterne

The Green's function formalism in Condensed Matter Physics is reviewed within the equation of motion approach. Composite operators and their Green's functions naturally appear as building blocks of generalized perturbative approaches and…

Statistical Mechanics · Physics 2007-05-23 Ferdinando Mancini , Adolfo Avella

A stochastic conjugate gradient method for approximation of a function is proposed. The proposed method avoids computing and storing the covariance matrix in the normal equations for the least squares solution. In addition, the method…

Numerical Analysis · Mathematics 2013-02-11 Hong Jiang , Paul Wilford

Higher Green functions are real-valued functions of two variables on the upper half plane which are bi-invariant under the action of a congruence subgroup, have logarithmic singularity along the diagonal, but instead of the usual equation…

Number Theory · Mathematics 2008-04-22 Anton Mellit

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

Inverse design enables automating the discovery and optimization of devices achieving performance significantly exceeding that of traditional human-engineered designs. However, existing methodologies to inverse-design electromagnetic…

Computational Physics · Physics 2026-01-30 Jui-Hung Sun , Mohamed Elsawaf , Yifei Zheng , Ho-Chun Lin , Chia Wei Hsu , Constantine Sideris

Recent trends of ab initio studies and progress in methodologies for electronic structure calculations of strongly correlated electron systems are discussed. The interest for developing efficient methods is motivated by recent discoveries…

Strongly Correlated Electrons · Physics 2010-12-06 Masatoshi Imada , Takashi Miyake

A new analytical operator method is discussed which solves linear ordinary differential equations with regular singularities. Solutions are obtained in analytic series form and also in Mellin-Barnes-type contour integral form. Exact series…

Mathematical Physics · Physics 2009-02-06 Wrick Sengupta

Non equilibrium Green's function methods are regularly used to calculate current and charge densities in nanoscale (both molecular and semiconductor) conductors under bias. This method is mainly used for ballistic conduction but may be…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 M. Paulsson

This paper presents a new methodology for the solution of problems of two- and three-dimensional acoustic scattering (and, in particular, two-dimensional electromagnetic scattering) by obstacles and defects in presence an arbitrary number…

Numerical Analysis · Mathematics 2017-08-23 Oscar P. Bruno , Carlos Pérez-Arancibia

We present a general formula for the particular solution of an inhomogeneous linear difference equation with variable coefficients. The answer is expressed as a weighted sum of fundamental solutions of the associated linear difference…

Combinatorics · Mathematics 2025-03-26 S. R. Mane

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