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While Landauer's Principle sets a lower bound for the work required for a computation, that work is recoverable for efficient computations. However, practical physical computers, such as modern digital computers or biochemical systems, are…

Statistical Mechanics · Physics 2021-04-27 Alexander B. Boyd , Paul M. Riechers , Gregory W. Wimsatt , James P. Crutchfield , Mile Gu

Machine learning opens new avenues for modelling correlated materials. Quantum embedding approaches, such as the dynamical mean-field theory (DMFT), provide corrections to first-principles calculations for strongly correlated materials,…

Computational Physics · Physics 2021-12-01 Evan Sheridan , Christopher Rhodes , Francois Jamet , Ivan Rungger , Cedric Weber

We explore the use of exact diagonalization methods for solving the self consistent equations of the cellular dynamical mean field theory (CDMFT) for the one dimensional regular and extended Hubbard models. We investigate the nature of the…

Strongly Correlated Electrons · Physics 2007-05-23 C. J. Bolech , S. S. Kancharla , G. Kotliar

We propose a non-linear, hybrid quantum-classical scheme for simulating non-equilibrium dynamics of strongly correlated fermions described by the Hubbard model in a Bethe lattice in the thermodynamic limit. Our scheme implements…

Quantum Physics · Physics 2016-09-14 J. M. Kreula , S. R. Clark , D. Jaksch

We explore the non-equilibrium dynamics of a one-dimensional Fermi-Hubbard system as a sensitive testbed for the capabilities of the time-dependent two-particle reduced density matrix (TD2RDM) theory to accurately describe time-dependent…

Strongly Correlated Electrons · Physics 2024-02-06 Stefan Donsa , Fabian Lackner , Joachim Burgdörfer , Michael Bonitz , Benedikt Kloss , Angel Rubio , Iva Březinová

We study the non-Markovian dynamics of a qubit made up of a two-level atom interacting with an electromagnetic field (EMF) initially at finite temperature. Unlike most earlier studies where the bath is assumed to be fixed, we study the…

Quantum Physics · Physics 2009-11-10 S. Shresta , C. Anastopoulos , A. Dragulescu , B. L. Hu

The thermalization of isolated quantum many-body systems is deeply related to fundamental questions of quantum information theory. While integrable or many-body localized systems display non-ergodic behavior due to extensively many…

We present an accurate and efficient finite-difference formulation and parallel implementation of Kohn-Sham Density (Operator) Functional Theory (DFT) for non periodic systems embedded in a bulk environment. Specifically, employing…

Computational Physics · Physics 2020-11-30 Swarnava Ghosh , Kaushik Bhattacharya

For the simulation of equilibrium states and finite-temperature response functions of strongly-correlated quantum many-body systems, we compare the efficiencies of two different approaches in the framework of the density matrix…

Strongly Correlated Electrons · Physics 2017-01-03 Moritz Binder , Thomas Barthel

We study the effect of spatially nonlocal correlations on the nonequilibrium dynamics of interacting fermions by constructing the nonequilibrium dynamical cluster theory, a cluster generalization of the nonequilibrium dynamical mean-field…

Strongly Correlated Electrons · Physics 2015-07-13 Naoto Tsuji , Peter Barmettler , Hideo Aoki , Philipp Werner

Dynamical mean-field theory (DMFT) provides an optimal local approximation for correlated lattice systems by mapping the lattice onto a self-consistent effective impurity model. To account for the missing long-range correlations, we propose…

Strongly Correlated Electrons · Physics 2026-03-04 S. D. Semenov , A. I. Lichtenstein , A. N. Rubtsov

We present TTCF4LAMMPS, a toolkit for performing non-equilibrium molecular dynamics (NEMD) simulations to study fluid behaviour at low shear rates using the LAMMPS software. By combining direct NEMD simulations and the transient-time…

Soft Condensed Matter · Physics 2023-12-07 Luca Maffioli , James P. Ewen , Edward R. Smith , Sleeba Varghese , Peter J. Daivis , Daniele Dini , B. D. Todd

Simulations of interacting electrons and bosons out of equilibrium, starting from first principles and aiming at realistic multiscale scenarios, is a grand theoretical challenge. Here, using the formalism of nonequilibrium Green's functions…

Strongly Correlated Electrons · Physics 2022-04-06 Yaroslav Pavlyukh , Enrico Perfetto , Daniel Karlsson , Robert van Leeuwen , Gianluca Stefanucci

Correlated classical and quantum many-particle systems out of equilibrium are of high interest in many fields, including dense plasmas, correlated solids, and ultracold atoms. Accurate theoretical description of these systems is challenging…

Statistical Mechanics · Physics 2026-04-02 Erik Schroedter , Michael Bonitz

Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under external time-dependent perturbations such as laser fields. In this work, we present a machine learning approach to accelerate…

Materials Science · Physics 2025-12-02 Karan Shah , Attila Cangi

We investigate the dynamical and analytical consequences of truncating the Gr\"unwald--Letnikov memory term in a fractional Duffing oscillator. The truncated memory is treated not merely as a computational approximation, but as a…

Chaotic Dynamics · Physics 2026-05-28 Mattia Coccolo

A major advance in density-matrix renormalization group (DMRG) calculations has been achieved by the invention of highly efficient DMRG techniques for the simulation of real-time dynamics of strongly correlated quantum systems in one…

Strongly Correlated Electrons · Physics 2007-05-23 U. Schollwoeck , S. R. White

We investigate an energy flow in an extended Holstein model describing electron systems coupled to hot-phonons and heat-bath phonons. To analyze the relaxation process after the photo-excitation of electrons, we employ the nonequilibrium…

Strongly Correlated Electrons · Physics 2023-11-07 Ken Inayoshi , Akihisa Koga , Yuta Murakami

Compute-in-memory accelerators built upon non-volatile memory devices excel in energy efficiency and latency when performing deep neural network (DNN) inference, thanks to their in-situ data processing capability. However, the stochastic…

Machine Learning · Computer Science 2025-08-19 Yifan Qin , Zheyu Yan , Dailin Gan , Jun Xia , Zixuan Pan , Wujie Wen , Xiaobo Sharon Hu , Yiyu Shi

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
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