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Within the framework of time-dependent density functional theory combined with the Korringa-Kohn-Rostoker Green function formalism, we present a real space methodology to investigate dynamical magnetic excitations from first-principles. We…

Mesoscale and Nanoscale Physics · Physics 2015-05-20 S. Lounis , A. T. Costa , R. B. Muniz , D. L. Mills

We study multi-particle interactive quantum disordered systems on a polynomially-growing countable connected graph (Z,E). The novelty is to give localization bounds uniform in finite or infinite volumes (subgraphs) in Z^N as well as for the…

Mathematical Physics · Physics 2014-04-16 Victor Chulaevsky , Yuri Suhov

We establish, through numerical calculations and comparisons with a recursive Green's function based implementation of the Landauer-B\"uttiker formalism, an efficient method for studying Anderson localization in quasi-one-dimensional and…

Mesoscale and Nanoscale Physics · Physics 2014-02-25 Andreas Uppstu , Zheyong Fan , Ari Harju

We study the persistence of localization for a strongly disordered tight-binding Anderson model on the lattice $\mathbb{Z}^d$, periodically driven on each site. Under two different sets of conditions, we show that Anderson localization…

Mathematical Physics · Physics 2016-07-26 Raphael Ducatez , François Huveneers

We propose a simplified version of the Multi-Scale Analysis of tight-binding Anderson models with strongly mixing random potentials which leads directly to uniform exponential bounds on decay of eigenfunctions in arbitrarily large finite…

Mathematical Physics · Physics 2012-05-08 Victor Chulaevsky

A semi-analytical dynamical mean-field approximation (DMA) has been developed for large but finite $N$-unit active rotator (AR) networks subject to individual white noises. Assuming weak noises and the Gaussian distribution of state…

Disordered Systems and Neural Networks · Physics 2007-05-23 Hideo Hasegawa

A reformulation of site-occupation embedding theory (SOET) in terms of Green's functions is presented. Referred to as site-occupation--Green's function embedding theory (SOGET), this novel extension of density-functional theory for model…

Strongly Correlated Electrons · Physics 2019-11-07 Laurent Mazouin , Matthieu Saubanère , Emmanuel Fromager

An accurate expression of the kinetic energy density of an electronic distribution in terms of the single particle reduced density matrix for atomic and molecular systems is a long-standing problem in electron structure theory. Existing…

Chemical Physics · Physics 2024-10-30 Priya , Mainak Sadhukhan

A new approach to detect change points based on differential smoothing and multiple testing is presented for long data sequences modeled as piecewise constant functions plus stationary ergodic Gaussian noise. As an application of the STEM…

Statistics Theory · Mathematics 2019-11-20 Dan Cheng , Zhibing He , Armin Schwartzman

A major goal of dynamical systems theory is the search for simplified descriptions of the dynamics of a large number of interacting states. For overwhelmingly complex dynamical systems, the derivation of a reduced description on the entire…

Physics and Society · Physics 2020-06-05 Yun William Yu , Jean-Charles Delvenne , Sophia N. Yaliraki , Mauricio Barahona

A statistical theory of the coupling between a quantum emitter and Anderson-localized cavity modes is presented based on a dyadic Green's function formalism. The probability of achieving the strong light-matter coupling regime is extracted…

Quantum Physics · Physics 2013-09-26 Henri Thyrrestrup , Stephan Smolka , Luca Sapienza , Peter Lodahl

In this paper, we describe a novel application of sigma-point methods to continuous-discrete filtering. In principle, the nonlinear continuous- discrete filtering problem can be solved exactly. In practice, the solution contains terms that…

Computation · Statistics 2015-06-15 Simon Lyons , Simo Särkkä , Amos Storkey

Our first result is a stochastic sewing lemma with quantitative estimates for mild incremental processes, with which we study SPDEs driven by fractional Brownian motions in a random environment. We obtain uniform $L^p$-bounds. Our second…

Probability · Mathematics 2023-03-07 Xue-Mei Li , Julian Sieber

We consider discrete one-dimensional Schr\"odinger operators with random potentials obtained via a block code applied to an i.i.d. sequence of random variables. It is shown that, almost surely, these operators exhibit spectral and dynamical…

Spectral Theory · Mathematics 2025-04-14 David Damanik , Anton Gorodetski , Victor Kleptsyn

Motivated by the link between Anderson localisation on high-dimensional graphs and many-body localisation, we study the effect of periodic driving on Anderson localisation on random trees. The time dependence is eliminated in favour of an…

Disordered Systems and Neural Networks · Physics 2021-03-31 Sthitadhi Roy , Roderich Moessner , Achilleas Lazarides

We investigate and compare the particle number fluctuations in the putative many-body localized (MBL) phase of a spinless fermion model with potential disorder and nearest-neighbor interactions with those in the non-interacting case…

Disordered Systems and Neural Networks · Physics 2022-01-26 Maximilian Kiefer-Emmanouilidis , Razmik Unanyan , Michael Fleischhauer , Jesko Sirker

Analytic continuation (AC) from imaginary-time Green's function to spectral function is essential in the numerical analysis of dynamical properties in quantum many-body systems. However, this process faces a fundamental challenge: it is an…

Strongly Correlated Electrons · Physics 2024-09-04 Yuichi Motoyama , Hiroshi Shinaoka , Junya Otsuki , Kazuyoshi Yoshimi

We extend the bootstrap multi-scale analysis developed by Germinet and Klein to the multi-particle Anderson model, obtaining Anderson localization, dynamical localization, and decay of eigenfunction correlations.

Mathematical Physics · Physics 2015-06-12 Abel Klein , Son T. Nguyen

Anderson acceleration (AA) is an extrapolation technique designed to speed-up fixed-point iterations like those arising from the iterative training of DL models. Training DL models requires large datasets processed in randomly sampled…

Machine Learning · Computer Science 2021-10-29 Massimiliano Lupo Pasini , Junqi Yin , Viktor Reshniak , Miroslav Stoyanov

We consider the multi-particle Anderson tight-binding model and prove that its lower spectral edge is non-random under some mild assumptions on the inter-particle interaction and the random external potential. We also adapt to the low…

Mathematical Physics · Physics 2013-12-30 Trésor Ekanga
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