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Factorizing low-rank matrices is a problem with many applications in machine learning and statistics, ranging from sparse PCA to community detection and sub-matrix localization. For probabilistic models in the Bayes optimal setting, general…

Information Theory · Computer Science 2018-12-07 Jean Barbier , Mohamad Dia , Nicolas Macris , Florent Krzakala , Lenka Zdeborová

The Kerr-Schild form provides a natural way of realizing the classical double copy that relates exact solutions in general relativity to exact solutions in gauge theory. In this paper, we examine the asymptotic structure of Kerr-Schild…

General Relativity and Quantum Cosmology · Physics 2022-01-26 Pujian Mao , Weicheng Zhao

Graphical models use the intuitive and well-studied methods of graph theory to implicitly represent dependencies between variables in large systems. They can model the global behaviour of a complex system by specifying only local factors.…

Artificial Intelligence · Computer Science 2015-08-21 Siamak Ravanbakhsh

We introduce a highly structured family of hard satisfiable 3-SAT formulas corresponding to an ordered spin-glass model from statistical physics. This model has provably "glassy" behavior; that is, it has many local optima with large energy…

Statistical Mechanics · Physics 2012-10-19 Haixia Jia , Cristopher Moore , Bart Selman

Using elementary rigorous methods we prove the existence of a clustered phase in the random $K$-SAT problem, for $K\geq 8$. In this phase the solutions are grouped into clusters which are far away from each other. The results are in…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. Mezard , T. Mora , R. Zecchina

Symmetry considerations and a direct, Hubbard-Stratonovich type, derivation are used to construct a replica field-theory relevant to the study of the spin glass transition of short range models in a magnetic field. A mean-field treatment…

Disordered Systems and Neural Networks · Physics 2009-11-07 T. Temesvari , C. De Dominicis , I. R. Pimentel

We analyze the replica-symmetry-breaking construction in the Sherrington-Kirkpatrick model of a spin glass. We present a general scheme for deriving an exact asymptotic behavior near the critical temperature of the solution with an…

Disordered Systems and Neural Networks · Physics 2008-09-16 V. Janis , A. Klic

The mean field theory of a spin glass with a specific form of nearest and next nearest neighbor interactions is investigated. Depending on the sign of the interaction matrix chosen we either find the continuous replica symmetry breaking…

Disordered Systems and Neural Networks · Physics 2007-05-23 D. S. Dean , F. Ritort

A scaling theory of replica symmetry breaking (RSB) in the SK-model is presented in the framework of critical phenomena for the scaling regime of small inverse RSB-orders, small temperatures, small magnetic fields, and near opposite…

Disordered Systems and Neural Networks · Physics 2009-11-13 Reinhold Oppermann , Manuel J. Schmidt

This is a review to appear as a contribution to the edited volume "Spin Glass Theory & Far Beyond - Replica Symmetry Breaking after 40 Years", World Scientific. It showcases a selection of contributions from the spin glass community at…

Disordered Systems and Neural Networks · Physics 2022-05-03 Erik Aurell , Jean Barbier , Aurelien Decelle , Roberto Mulet

Facilitated or kinetically constrained spin models (KCSM) are a class of interacting particle systems reversible w.r.t. to a simple product measure. Each dynamical variable (spin) is re-sampled from its equilibrium distribution only if the…

Probability · Mathematics 2012-10-04 Nicoletta Cancrini , Fabio Martinelli , Cyril Roberto , Cristina Toninelli

We study the problem of testing and recovering $k$-clique Ferromagnetic mean shift in the planted Sherrington-Kirkpatrick model (i.e., a type of spin glass model) with $n$ spins. The planted SK model -- a stylized mixture of an uncountable…

Statistics Theory · Mathematics 2024-03-25 Yihan He , Han Liu , Jianqing Fan

We study the Convex Set Disjointness (CSD) problem, where two players have input sets taken from an arbitrary fixed domain~$U\subseteq \mathbb{R}^d$ of size $\lvert U\rvert = n$. Their mutual goal is to decide using minimum communication…

Data Structures and Algorithms · Computer Science 2019-09-10 Mark Braverman , Gillat Kol , Shay Moran , Raghuvansh R. Saxena

We review the understanding of the random constraint satisfaction problems, focusing on the q-coloring of large random graphs, that has been achieved using the cavity method of the physicists. We also discuss the properties of the phase…

Computational Complexity · Computer Science 2008-02-04 Florent Krzakala , Lenka Zdeborová

We study the quenched complexity in spin-glass mean-field models satisfying the Becchi-Rouet-Stora-Tyutin supersymmetry. The outcome of such study, consistent with recent numerical results, allows, in principle, to conjecture the absence of…

Disordered Systems and Neural Networks · Physics 2009-11-10 A. Crisanti , L. Leuzzi , G. Parisi , T. Rizzo

We describe simulations of the quantum dynamics of a confocal cavity QED system that realizes an intrinsically driven-dissipative spin glass. A close connection between open quantum dynamics and replica symmetry breaking is established, in…

We derive spherically symmetric solutions of the classical \lambda-R model, a minimal, anisotropic modification of general relativity with a preferred foliation and two local degrees of freedom. Starting from a 3 + 1 decomposition of the…

General Relativity and Quantum Cosmology · Physics 2017-08-30 Renate Loll , Luis Pires

This chapter introduces a variety of spin glass models, beyond the simple Sherrington-Kirkpatrick (SK) version, that have led to enriched understanding and application.

Disordered Systems and Neural Networks · Physics 2022-08-19 David Sherrington , Jairo de Almeida

The symmetry method is used to derive solutions of Einstein's equations for fluid spheres using an isotropic metric and a velocity four vector that is non-comoving. Initially the Lie, classical approach is used to review and provide a…

General Relativity and Quantum Cosmology · Physics 2010-05-12 Ron Wiltshire

Random $K$-satisfiability ($K$-SAT) is a paradigmatic model system for studying phase transitions in constraint satisfaction problems and for developing empirical algorithms. The statistical properties of the random $K$-SAT solution space…

Disordered Systems and Neural Networks · Physics 2020-07-08 Han Zhao , Hai-Jun Zhou