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Quantum many-body theory has witnessed tremendous progress in various fields, ranging from atomic and solid-state physics to quantum chemistry and nuclear structure. Due to the inherent computational burden linked to the ab initio treatment…

The bulk macroscopic response of a system of particles or inclusions with field-induced forces is studied. The susceptibilities and transport coefficients in such a system are expressed as averages of a multiple scattering expansion. A…

Statistical Mechanics · Physics 2009-11-13 P. Szymczak , B. Cichocki

Electronic-structure functionals that include screening effects, such as Hubbard or Koopmans' functionals, require to describe the response of a system to the fractional addition or removal of an electron from an orbital or a manifold.…

Computational Physics · Physics 2018-10-02 Nicola Colonna , Ngoc Linh Nguyen , Andrea Ferretti , Nicola Marzari

We apply renormalisation-group methods to two-body scattering by a combination of known long-range and unknown short-range potentials. We impose a cut-off in the basis of distorted waves of the long-range potential and identify possible…

High Energy Physics - Phenomenology · Physics 2009-11-07 Thomas Barford , Michael C. Birse

The functional renormalization group has become a widely used tool for the analysis of the leading low-temperature correlations in weakly to moderately coupled many-fermion lattice systems. A bottleneck for quantitatively more precise…

Strongly Correlated Electrons · Physics 2018-08-15 Timo Reckling , Carsten Honerkamp

In this paper, a novel linear method for shape reconstruction is proposed based on the generalized multiple measurement vectors (GMMV) model. Finite difference frequency domain (FDFD) is applied to discretized Maxwell's equations, and the…

Signal Processing · Electrical Eng. & Systems 2019-06-27 Shilong Sun , Bert Jan Kooij , Alexander G. Yarovoy , Tian Jin

We consider the problem of reconstructing signals and images from periodic nonlinearities. For such problems, we design a measurement scheme that supports efficient reconstruction; moreover, our method can be adapted to extend to…

Machine Learning · Statistics 2017-10-03 Viraj Shah , Mohammadreza Soltani , Chinmay Hegde

In the last years, the success of kernel-based regularisation techniques in solving impulse response modelling tasks has revived the interest on linear system identification. In this work, an alternative perspective on the same problem is…

Systems and Control · Computer Science 2016-10-25 Anna Marconato , Maarten Schoukens , Johan Schoukens

We present a method for treatment of three charged particles. The proposed method has universal character and is applicable both for bound and continuum states. A finite rank approximation is used for Coulomb potential in three-body system…

Nuclear Theory · Physics 2010-12-16 Vladimir B. Belyaev , Andrey A. Naumkin

Amorphous particulate matter constitutes a wide range of natural and synthetic materials. Despite this ubiquity, the way in which these systems' disordered microstructure couples to their often subtle and complex dynamical behavior is not…

Soft Condensed Matter · Physics 2026-03-09 Erin G. Teich , Jason Z. Kim , Dani S. Bassett

Scalable characterization of quantum processors is crucial for mitigating noise and imperfections. While randomized measurement protocols enable efficient access to local observables, inferring a globally consistent description of…

Quantum Physics · Physics 2026-03-10 Zidu Liu , Dominik S. Wild

The aim of this paper is to investigate the use of an entropic projection method for the iterative regularization of linear ill-posed problems. We derive a closed form solution for the iterates and analyze their convergence behaviour both…

Optimization and Control · Mathematics 2020-01-29 Martin Burger , Elena Resmerita , Martin Benning

Deep-learning-based nonlinear system identification has shown the ability to produce reliable and highly accurate models in practice. However, these black-box models lack physical interpretability, and a considerable part of the learning…

Machine Learning · Computer Science 2025-07-15 Bendegúz M. Györök , Jan H. Hoekstra , Johan Kon , Tamás Péni , Maarten Schoukens , Roland Tóth

The density-matrix renormalization-group (DMRG) algorithm is extended to treat time-dependent problems. The method provides a systematic and robust tool to explore out-of-equilibrium phenomena in quantum many-body systems. We illustrate the…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 M. A. Cazalilla , J. B. Marston

We derive a closed equation of motion for the current density of an inhomogeneous quantum many-body system under the assumption that the time-dependent wave function can be described as a geometric deformation of the ground-state wave…

Other Condensed Matter · Physics 2015-05-14 Xianlong Gao , Jianmin Tao , G. Vignale , I. V. Tokatly

We propose a systematic approach to the non-equilibrium dynamics of strongly interacting many-body quantum systems, building upon the standard perturbative expansion in the Coulomb interaction. High order series are derived from the Keldysh…

Strongly Correlated Electrons · Physics 2019-10-16 Corentin Bertrand , Serge Florens , Olivier Parcollet , Xavier Waintal

Event reconstruction is a central step in many particle physics experiments, turning detector observables into parameter estimates; for example estimating the energy of an interaction given the sensor readout of a detector. A corresponding…

High Energy Physics - Experiment · Physics 2023-01-11 Philipp Eller , Aaron Fienberg , Jan Weldert , Garrett Wendel , Sebastian Böser , D. F. Cowen

Coupled cluster theory is the method of choice for weakly correlated systems. But in the strongly correlated regime, it faces a symmetry dilemma, where it either completely fails to describe the system, or has to artificially break certain…

Chemical Physics · Physics 2020-05-14 Yiheng Qiu , Thomas M. Henderson , Jinmo Zhao , Gustavo E. Scuseria

We develop a novel multi-configurational Symmetrized Projector Quantum Monte Carlo (MSPQMC) method to calculate excited state properties of Hubbard models. We compare the MSPQMC results for finite Hubbard chains with exact results (where…

Condensed Matter · Physics 2009-10-28 Bhargavi Srinivasan , S. Ramasesha , H. R. Krishnamurthy

The renormalization method is specifically aimed at connecting theories describing physical processes at different length scales and thereby connecting different theories in the physical sciences. The renormalization method used today is…

Statistical Mechanics · Physics 2011-02-21 Leo P. Kadanoff
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