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We present a simple combinatorial framework for establishing approximate tensorization of variance and entropy in the setting of spin systems (a.k.a. undirected graphical models) based on balanced separators of the underlying graph. Such…

Data Structures and Algorithms · Computer Science 2023-07-18 Zongchen Chen

Generalized matrix approximation plays a fundamental role in many machine learning problems, such as CUR decomposition, kernel approximation, and matrix low rank approximation. Especially with today's applications involved in larger and…

Numerical Analysis · Computer Science 2016-09-09 Haishan Ye , Qiaoming Ye , Zhihua Zhang

In a Hilbert setting, for convex differentiable optimization, we develop a general framework for adaptive accelerated gradient methods. They are based on damped inertial dynamics where the coefficients are designed in a closed-loop way.…

Optimization and Control · Mathematics 2025-01-28 Hedy Attouch , Radu Ioan Bot , Dang-Khoa Nguyen

We consider dynamical low-rank approximations to parabolic problems on higher-order tensor manifolds in Hilbert spaces. In addition to existence of solutions and their stability with respect to perturbations to the problem data, we show…

Numerical Analysis · Mathematics 2025-05-19 Markus Bachmayr , Henrik Eisenmann , André Uschmajew

We develop a geometric version of the inverse problem of the calculus of variations for discrete mechanics and constrained discrete mechanics. The geometric approach consists of using suitable Lagrangian and isotropic submanifolds. We also…

Differential Geometry · Mathematics 2018-05-09 María Barbero-Liñán , Marta Farré Puiggalí , Sebastián Ferraro , David Martín de Diego

In this paper we propose a wide class of truncated stochastic approximation procedures with moving random bounds. While we believe that the proposed class of procedures will find its way to a wider range of applications, the main motivation…

Methodology · Statistics 2012-05-04 Teo Sharia

Hybrid stochastic differential equations are a useful tool to model continuously varying stochastic systems which are modulated by a random environment that may depend on the system state itself. In this paper, we establish the pathwise…

Probability · Mathematics 2022-11-04 Hansjoerg Albrecher , Oscar Peralta

Model approximations are common practice when estimating structural or quasi-structural models. The paper considers the econometric properties of estimators that utilize projections to reimpose information about the exact model in the form…

Econometrics · Economics 2024-03-05 Andreas Tryphonides

Symmetry is a fundamentally important concept in many branches of physics. In this work, we discuss two types of symmetries, external symmetry and internal symmetry, which appear frequently in controlled quantum spin chains and apply them…

Quantum Physics · Physics 2016-12-06 Xiaoting Wang , Daniel Burgarth , Sophie Schirmer

We show that the correlations in stochastic outputs of time-distributed weak measurements can be used to study the dynamics of an individual quantum object, with a proof-of-principle setup based on small Faraday rotation caused by a single…

Mesoscale and Nanoscale Physics · Physics 2010-01-20 R. -B. Liu , Shu-Hong Fung , Hok-Kin Fung , A. N. Korotkov , L. J. Sham

In the 1970s a new paradigm was introduced that interacting quenched systems, such as a spin-glass, have a phase transition in which long time memory of spatial patterns is realized without spatial correlations. The principal methods to…

A comparative analysis of a description of spin dynamics in the cylindrical and Frenet-Serret coordinate systems is carried out. An equivalence of these two systems is shown. A possibility of efficient use of the cylindrical coordinate…

Accelerator Physics · Physics 2015-02-23 Alexander J. Silenko

The relativistic Wigner function for spin 1/2 particles is the subject of active research due to diverse applications. However, further progress is hindered by the fabulous complexity of the integro-differential equations of motion. We…

Quantum Physics · Physics 2012-08-23 Renan Cabrera , Denys I. Bondar , Herschel A. Rabitz

There has been recent interest in the relaxational modes of small-scale fully connected systems of aligning self-propelled particles (Spera et al., Phys. Rev. Lett. {\bf 132}: 078301 (2024)). We revisit the classical connection between…

Statistical Mechanics · Physics 2026-03-25 Tara Steinhöfel , Horst-Holger Boltz , Thomas Ihle

A relaxation-function theory for the dynamic spin susceptibility in the $t$--$J$ model is presented. By a sum-rule-conserving generalized mean-field approximation (GMFA), the two-spin correlation functions of arbitrary range, the staggered…

Strongly Correlated Electrons · Physics 2015-05-13 A. A. Vladimirov , D. Ihle , N. M. Plakida

Based on the weighted and shifted Gr\"{u}nwald difference (WSGD) operators [24], we further construct the compact finite difference discretizations for the fractional operators. Then the discretization schemes are used to approximate the…

Numerical Analysis · Mathematics 2014-01-30 Han Zhou , WenYi Tian , Weihua Deng

We show results of simulations of a weakly driven four dimensional Edwards- Anderson spin glass, which presents clear signatures of dynamical ultrametricity at low temperatures. The presence of a hierarchical organization of time scales is…

Disordered Systems and Neural Networks · Physics 2009-10-31 Daniel A. Stariolo

Multi-material design optimization problems can, after discretization, be solved by the iterative solution of simpler sub-problems which approximate the original problem at an expansion point to first order. In particular, models…

Numerical Analysis · Mathematics 2026-04-01 Peter Gangl , Nico Nees , Michael Stingl

In this paper we provide a rigorous mathematical foundation for continuous approximations of a class of systems with piece-wise continuous functions. By using techniques from the theory of differential inclusions, the underlying piece-wise…

Chaotic Dynamics · Physics 2014-08-20 Marius-F. Danca

A powerful existing technique for evaluating statistical mechanical quantities in two-dimensional Ising models is based on constructing a matrix representing the nearest neighbor spin couplings and then evaluating the Pfaffian of the…

Disordered Systems and Neural Networks · Physics 2013-04-16 Creighton K. Thomas , A. Alan Middleton