English
Related papers

Related papers: Localization properties of the sparse Barrat-M\'ez…

200 papers

This paper summarizes some work I've been doing on eigenvalue correlators of Random Matrix Models which show some interesting behaviour. First we consider matrix models with gaps in there spectrum or density of eigenvalues. The…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 N. Deo

We introduce a new method for sparse principal component analysis, based on the aggregation of eigenvector information from carefully-selected axis-aligned random projections of the sample covariance matrix. Unlike most alternative…

Methodology · Statistics 2019-05-07 Milana Gataric , Tengyao Wang , Richard J. Samworth

We theoretically study the Anderson localization of a matter wave packet in a one-dimensional disordered potential. We develop an analytical model which includes the initial phase-space density of the matter wave and the spectral broadening…

Disordered Systems and Neural Networks · Physics 2011-03-08 Marie Piraud , Pierre Lugan , Philippe Bouyer , Alain Aspect , Laurent Sanchez-Palencia

We study diffusion on a substrate with permanent traps distributed with critical positional correlation, modeled by their placement on the perimeters of a critical percolation cluster. We perform a numerical analysis of the vibrational…

Condensed Matter · Physics 2009-10-28 Sonali Mukherjee , Hisao Nakanishi

This review presents a unified view on the problem of Anderson localization in one-dimensional weakly disordered systems with short-range and long-range statistical correlations in random potentials. The following models are analyzed: the…

Disordered Systems and Neural Networks · Physics 2012-05-15 F. M. Izrailev , A. A. Krokhin , N. M. Makarov

We review recent progress in analysing wave scattering in systems with both intrinsic chaos and/or disorder and internal losses, when the scattering matrix is no longer unitary. By mapping the problem onto a nonlinear supersymmetric…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Y. V. Fyodorov , D. V. Savin , H. -J. Sommers

Sparse support recovery arises in many applications in communications and signal processing. Existing methods tackle sparse support recovery problems for a given measurement matrix, and cannot flexibly exploit the properties of sparsity…

Information Theory · Computer Science 2019-10-11 Shuaichao Li , Wanqing Zhang , Ying Cui , Hei Victor Cheng , Wei Yu

This paper introduces an elasticity reconstruction method based on local displacement observations of elastic bodies. Sparse reconstruction theory is applied to formulate the underdetermined inverse problems of elasticity reconstruction…

Machine Learning · Computer Science 2019-02-26 Megumi Nakao , Mitsuki Morita , Tetsuya Matsuda

We present a method to demonstrate Anderson localization in an optically induced randomized potential. By usage of computer controlled spatial light modulators, we are able to implement fully randomized nondiffracting beams of variable…

It is well-known that both branching random walk models and trap models can exhibit intermittency and localisation phenomena; the prototypical examples being the parabolic Anderson and Bouchaud trap models respectively. Our aim is to…

Probability · Mathematics 2017-03-21 Stephen Muirhead , Richard Pymar

The properties of the entanglement entropy (EE) in one-dimensional disordered interacting systems are studied. Anderson localization leaves a clear signature on the average EE, as it saturates on length scale exceeding the localization…

Mesoscale and Nanoscale Physics · Physics 2015-06-04 Richard Berkovits

Using numerical exact diagonalization, we study matrix elements of a local spin operator in the eigenbasis of two different nonintegrable quantum spin chains. Our emphasis is on the question to what extent local operators can be represented…

Statistical Mechanics · Physics 2020-10-27 Jonas Richter , Anatoly Dymarsky , Robin Steinigeweg , Jochen Gemmer

Phase retrieval can be expressed as one non-convex constrained optimization problem to identify one phase minimizer in the primal space. Many iterative transform techniques have been proposed to identify the minimizer, e.g., relaxed…

Optimization and Control · Mathematics 2021-12-22 Pengwen Chen

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

Localization phenomena permeate many branches of physics playing a fundamental role on dynamical processes evolving on heterogeneous networks. These localization analyses are frequently grounded, for example, on eigenvectors of adjacency or…

Physics and Society · Physics 2020-11-24 Diogo H. Silva , Silvio C. Ferreira

Sparse autoencoders provide a promising unsupervised approach for extracting interpretable features from a language model by reconstructing activations from a sparse bottleneck layer. Since language models learn many concepts, autoencoders…

Machine Learning · Computer Science 2024-06-07 Leo Gao , Tom Dupré la Tour , Henk Tillman , Gabriel Goh , Rajan Troll , Alec Radford , Ilya Sutskever , Jan Leike , Jeffrey Wu

The localization phenomena due to the random potential scattering is widely discussed in the electron and photon systems, where the theoretical approach is the nonlinear $\sigma$ model with the replica method or with the supersymmetry. In…

Disordered Systems and Neural Networks · Physics 2019-06-27 Shinobu Hikami

In this work we study the spectral properties of the adjacency matrix of critical Erd\"os-R\'enyi (ER) graphs, i.e. when the average degree is of order \log N. In a series of recent inspiring papers Alt, Ducatez, and Knowles have rigorously…

Disordered Systems and Neural Networks · Physics 2022-05-18 Marco Tarzia

The problem of estimating sparse eigenvectors of a symmetric matrix attracts a lot of attention in many applications, especially those with high dimensional data set. While classical eigenvectors can be obtained as the solution of a…

Machine Learning · Statistics 2016-11-03 Konstantinos Benidis , Ying Sun , Prabhu Babu , Daniel P. Palomar

We introduce novel characterizations for many-body phase transitions between delocalized and localized phases based on the system's sensitivity to boundary conditions. In particular, we change boundary conditions from periodic to…

Strongly Correlated Electrons · Physics 2021-01-27 Mohammad Pouranvari , Shiuan-Fan Liou