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Related papers: Quantum states in disordered media. I. Low-pass fi…

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In this paper, we propose two time-splitting finite element methods to solve the semiclassical nonlinear Schr\"odinger equation (NLSE) with random potentials. We then introduce the multiscale finite element method (MsFEM) to reduce the…

Numerical Analysis · Mathematics 2025-02-12 Panchi Li , Zhiwen Zhang

In this paper, approximate Linear Minimum Variance (LMV) filters for continuous-discrete state space models are introduced. The filters are obtained by means of a recursive approximation to the predictions for the first two moments of the…

Optimization and Control · Mathematics 2013-12-18 Juan Carlos Jimenez

Due to the anisotropy of quantum lossy channels one must choose optimal bases of input states for best estimating them. In this paper, we obtain that the equal probability Schr\"{o}dinger cat states are optimal for estimating a single lossy…

Quantum Physics · Physics 2007-05-23 Xian-Ting Liang

Nonlinear Schrodinger Equations (NLS) of the Hartree type occur in the modeling of quantum semiconductor devices. Their "semiclassical" limit of vanishing (scaled) Planck constant is both a mathematical challenge and practically relevant…

Analysis of PDEs · Mathematics 2007-05-23 Remi Carles , Norbert Mauser , Hans Peter Stimming

The Hartree-Fock based diagonalization is a computational method for the investigation of the low-energy properties of correlated electrons in disordered solids. The method is related to the quantum-chemical configuration interaction…

Disordered Systems and Neural Networks · Physics 2007-05-23 Michael Schreiber , Thomas Vojta

We describe how to use quantum linear algebra to simulate a physically realistic model of disordered non-interacting electrons. The physics of disordered electrons outside of one dimension challenges classical computation due to the…

Quantum Physics · Physics 2025-04-25 Jielun Chen , Garnet Kin-Lic Chan

The half-line one-dimensional Coulomb potential is possibly the simplest D-dimensional model with physical solutions which has been proved to be successful to describe the behaviour of Rydberg atoms in external fields and the dynamics of…

Mathematical Physics · Physics 2009-09-03 J. J. Omiste , R. J. Yanez , J. S. Dehesa

We present an efficient algorithm for the least squares parameter fitting optimized for component separation in multi-frequency CMB experiments. We sidestep some of the problems associated with non-linear optimization by taking advantage of…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-26 Rishi Khatri

Anderson localization is a universal interference phenomenon occurring when a wave evolves through a random medium and it has been observed in a great variety of physical systems, either quantum or classical. The recently developed…

Disordered Systems and Neural Networks · Physics 2022-11-30 David Colas , Cédric Bellis , Bruno Lombard , Régis Cottereau

Inverse scattering has a broad applicability in quantum mechanics, remote sensing, geophysical, and medical imaging. This paper presents a robust direct reduced order model (ROM) method for solving inverse scattering problems based on an…

Numerical Analysis · Mathematics 2023-11-29 Justin Baker , Elena Cherkaev , Vladimir Druskin , Shari Moskow , Mikhail Zaslavsky

Topic of the thesis is a theoretical description of the ultracold atomic gases in one- and two-dimensional optical lattices in the presence of the disorder leading to the Anderson localization. The disorder is created by interaction of the…

Quantum Gases · Physics 2017-07-19 Jan Major

A quantum particle can be localized in a disordered potential, the effect known as Anderson localization. In such a system, correlations of wave functions at very close energies may be described, due to Mott, in terms of a hybridization of…

Mesoscale and Nanoscale Physics · Physics 2012-01-17 D. A. Ivanov , M. A. Skvortsov , P. M. Ostrovsky , Ya. V. Fominov

This paper introduces factored conditional filters, new filtering algorithms for simultaneously tracking states and estimating parameters in high-dimensional state spaces. The conditional nature of the algorithms is used to estimate…

Artificial Intelligence · Computer Science 2024-07-10 Dawei Chen , Samuel Yang-Zhao , John Lloyd , Kee Siong Ng

Anderson localization is the ubiquitous phenomenon of inhibition of transport of classical and quantum waves in a disordered medium. In dimension one, it is well known that all states are localized, implying that the distribution of an…

Disordered Systems and Neural Networks · Physics 2022-06-14 Clément Hainaut , Jean-François Clément , Pascal Szriftgiser , Jean Claude Garreau , Adam Rançon , Radu Chicireanu

The formation of Stationary Localized states due to a nonlinear dimeric impurity embedded in a perfect 1-d chain is studied here using the appropriate Discrete Nonlinear Schr$\ddot{o}$dinger Equation. Furthermore, the nonlinearity has the…

Disordered Systems and Neural Networks · Physics 2009-10-28 B. C. Gupta , K. Kundu

Numerical approximation of quantum states via convex combinations of states with positive partial transposes (bi-PPT state) in multipartite systems constitutes a fundamental challenge in quantum information science. We reformulate this…

Mathematical Physics · Physics 2025-09-24 Jingwen Fan , Deren Han , Lin Chen

In this paper, we present a novel optimization algorithm designed specifically for estimating state-space models to deal with heavy-tailed measurement noise and constraints. Our algorithm addresses two significant limitations found in…

Signal Processing · Electrical Eng. & Systems 2024-11-19 Yifan Yu , Shengjie Xiu , Daniel P. Palomar

Disorder-free localization (DFL) is a phenomenon as striking as it appears to be simple: a translationally invariant state evolving under a disorder-free Hamiltonian failing to thermalize. It is predicted to occur in a number of quantum…

We propose a theoretical framework to analyze semi-supervised classification under the low density separation assumption in a high-dimensional regime. In particular, we introduce QLDS, a linear classification model, where the low density…

Machine Learning · Computer Science 2023-10-23 Vasilii Feofanov , Malik Tiomoko , Aladin Virmaux

Lattice reduction (LR) aided multiple-input-multiple-out (MIMO) linear detection can achieve the maximum receive diversity of the maximum likelihood detection (MLD). By emloying the most commonly used Lenstra, Lenstra, and L. Lovasz (LLL)…

Information Theory · Computer Science 2013-04-25 Keke Zu , Rodrigo C. de Lamare
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