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We study bipartite entanglement in a general one-particle state, and find that the linear entropy, quantifying the bipartite entanglement, is directly connected to the paricitpation ratio, charaterizing the state localization. The more…

Quantum Physics · Physics 2009-11-10 Haibin Li , Xiaoguang Wang , Bambi Hu

Analytical complexity of quantum wavefunction whose argument is extended into the complex plane provides an important information about the potentiality of manifesting complex quantum dynamics such as time-irreversibility, dissipation and…

Statistical Mechanics · Physics 2015-06-17 Hiroaki S. Yamada , Kensuke S. Ikeda

Localized patterns are coherent structures embedded in a quiescent state and occur in both discrete and continuous media across a wide range of applications. While it is well-understood how domain covering patterns (for example stripes and…

Pattern Formation and Solitons · Physics 2025-03-19 Jason J. Bramburger , Dan J. Hill , David J. B. Lloyd

Let a pure state \psi be chosen randomly in an NM-dimensional Hilbert space, and consider the reduced density matrix \rho of an N-dimensional subsystem. The bipartite entanglement properties of \psi are encoded in the spectrum of \rho. By…

Mathematical Physics · Physics 2013-05-16 Fabio Deelan Cunden , Paolo Facchi , Giuseppe Florio , Saverio Pascazio

This paper concerns spectral properties of linear Schr\"odinger operators under oscillatory high-amplitude potentials on bounded domains. Depending on the degree of disorder, we prove the existence of spectral gaps amongst the lowermost…

Numerical Analysis · Mathematics 2020-02-11 Robert Altmann , Patrick Henning , Daniel Peterseim

Anderson localization is a consequence of coherent interference of multiple scattering events in the presence of disorder, which leads to an exponential suppression of the transmission. The decay of the transmission is typically probed at a…

Mesoscale and Nanoscale Physics · Physics 2017-06-28 Hichem Eleuch , Michael Hilke , Richard MacKenzie

We study a class of dynamical networks modeled by linear and time-invariant systems which are described by state-space realizations. For these networks, we investigate the relations between various types of factorizations which preserve the…

Systems and Control · Electrical Eng. & Systems 2025-12-02 Şerban Sabău , Andrei Sperilă , Cristian Oară , Ali Jadbabaie

Theories of localised pattern formation are important to understand a broad range of natural patterns, but are less well-understood than more established mechanisms of domain-filling pattern formation. Here, we extend recent work on pattern…

Pattern Formation and Solitons · Physics 2025-07-22 Andrew L. Krause , Václav Klika , Edgardo Villar-Sepúlveda , Alan R. Champneys , Eamonn A. Gaffney

Motivated by the problem of Many-Body Localization and the recent numerical results for the level and eigenfunction statistics on the random regular graphs, a generalization of the Rosenzweig-Porter random matrix model is suggested that…

Disordered Systems and Neural Networks · Physics 2015-12-29 V. E. Kravtsov , I. M. Khaymovich , E. Cuevas , M. Amini

We explore the properties of discrete random Schroedinger operators in which the random part of the potential is supported on a sub-lattice. In particular, we provide new conditions on the sub-lattice under which Anderson localisation…

Mathematical Physics · Physics 2017-08-07 Alexander Elgart , Sasha Sodin

Motivated by experimental progress in cold atomic systems, we use and advance Localisation Landscape Theory (LLT), to examine two-dimensional systems with point-like random scatterers. We begin by showing that exact eigenstates cannot be…

Quantum Gases · Physics 2021-11-23 Sophie S. Shamailov , Dylan J. Brown , Thomas A. Haase , Maarten D. Hoogerland

Methods exploiting sparsity have been popular in imaging and signal processing applications including compression, denoising, and imaging inverse problems. Data-driven approaches such as dictionary learning and transform learning enable one…

Machine Learning · Computer Science 2018-02-05 Saiprasad Ravishankar , Anna Ma , Deanna Needell

We study the spatial structure of wave functions with exceptionally high local amplitudes in the Anderson model of localisation. By means of exact diagonalisations of finite systems, we obtain and analyse images of these wave functions: we…

Disordered Systems and Neural Networks · Physics 2009-11-07 V. Uski , B. Mehlig , M. Schreiber

We study the exploration of an Erd\"os-R\'enyi random graph by a respondent-driven sampling method, where discovered vertices reveal their neighbours. Some of them receive coupons to reveal in their turn their own neighbourhood. This leads…

Probability · Mathematics 2021-03-31 Anthony Cousien , Jean-Stéphane Dhersin , Viet Chi Tran , Thi Phuong Thuy Vo

Mixture models are widely used to fit complex and multimodal datasets. In this paper we study mixtures with high dimensional sparse latent parameter vectors and consider the problem of support recovery of those vectors. While parameter…

Machine Learning · Computer Science 2022-09-13 Arya Mazumdar , Soumyabrata Pal

We study localization properties of continuously monitored dynamics and associated measurement-induced phase transitions in disordered quantum many-body systems on the basis of the quantum trajectory approach. By calculating the fidelity…

Statistical Mechanics · Physics 2023-06-09 Kazuki Yamamoto , Ryusuke Hamazaki

Using projected entangled-pair states (PEPS) we analyze the localization properties of two-dimensional systems on a square lattice. We compare the dynamics found for three different disorder types: (i) quenched disorder, (ii) sum of two…

Disordered Systems and Neural Networks · Physics 2018-11-13 D. M. Kennes

A simple tight-binding model is used to illustrate how the time dependence of a state vector can be obtained from all the eigenvalues and eigenvectors of the Hamiltonian. The behavior of the eigenvalues and eigenvectors is studied for…

Physics Education · Physics 2015-06-26 Antonio Siber

We learn, in an unsupervised way, an embedding from sequences of radar images that is suitable for solving the place recognition problem with complex radar data. Our method is based on invariant instance feature learning but is tailored for…

Computer Vision and Pattern Recognition · Computer Science 2021-10-07 Matthew Gadd , Daniele De Martini , Paul Newman

We investigate the scaling properties of the two-dimensional (2D) Anderson model of localization with purely off-diagonal disorder (random hopping). Using the transfer-matrix method and finite-size scaling we compute the infinite-size…

Disordered Systems and Neural Networks · Physics 2015-06-24 Andrzej Eilmes , Rudolf A. Roemer