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Related papers: Optimization of Mean-field Spin Glasses

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We study an M-p-spin spin glass model with p=3 and M=3 in three dimensions using the Migdal-Kadanoff renormalization group approximation (MKA). In this version of the p-spin model, there are three (M=3) Ising spins on each site. At…

Statistical Mechanics · Physics 2012-03-20 Joonhyun Yeo , M. A. Moore

The Parisi formula for the free energy is among the crown jewels in the theory of spin glasses. We present a simpler proof of the lower bound in the case of the spherical mean-field model. Our method follows the TAP approach developed…

Probability · Mathematics 2024-05-03 Brice Huang , Mark Sellke

We construct and analyze a family of $M$-component vectorial spin systems which exhibit glass transitions and jamming within supercooled paramagnetic states without quenched disorder. Our system is defined on lattices with connectivity…

Statistical Mechanics · Physics 2018-06-27 Hajime Yoshino

The Sherrington--Kirkpatrick model of spin glasses, the Hopfield model of neural networks and the Ising spin glass are all models of binary data belonging to the one-parameter exponential family with quadratic sufficient statistic. Under…

Probability · Mathematics 2007-12-18 Sourav Chatterjee

We focus on spherical spin glasses whose Parisi distribution has support of the form $[0,q]$. For such models we construct paths from the origin to the sphere which consistently remain close to the ground-state energy on the sphere of…

Probability · Mathematics 2019-12-03 Eliran Subag

We consider the classical momentum- or velocity-dependent two-dimensional Hamiltonian given by $$\mathcal H_N = p_1^2 + p_2^2 +\sum_{n=1}^N \gamma_n(q_1 p_1 + q_2 p_2)^n ,$$ where $q_i$ and $p_i$ are generic canonical variables, $\gamma_n$…

Mathematical Physics · Physics 2023-01-06 Alfonso Blasco , Ivan Gutierrez-Sagredo , Francisco J. Herranz

Aim of this work is not trying to explore a macroscopic behavior of some recent model in statistical mechanics but showing how some recent techniques developed within the framework of spin glasses do work on simpler model, focusing on the…

Disordered Systems and Neural Networks · Physics 2009-11-13 Adriano Barra

Critical slowing down dynamics of supercooled glass-forming liquids is usually understood at the mean-field level in the framework of Mode Coupling Theory, providing a two-time relaxation scenario and power-law behaviors of the time…

Disordered Systems and Neural Networks · Physics 2013-01-30 Ulisse Ferrari , Luca Leuzzi , Giorgio Parisi , Tommaso Rizzo

We study the d-dimensional random Ising model using a Bethe-Peierls approximation in the framework of the replica method. We take into account the correct interaction only inside replicated clusters of spins. Our ansatz is that the…

Condensed Matter · Physics 2009-10-28 M. Serva , G. Paladin

We present a model of spheres moving in a high-dimensional compact space. We relate it to a mixed matrix model with a $O(N)$ invariant model plus a $P(N)$ invariant perturbation. We then study the low pressure regime by performing a…

Condensed Matter · Physics 2009-10-28 Leticia F. Cugliandolo , J. Kurchan , Remi Monasson , Giorgio Parisi

Within the replica approach to mean-field spin-glasses the transition from ergodic high-temperature behaviour to the glassy low-temperature phase is marked by the instability of the replica-symmetric saddle-point. For general spin-glass…

Disordered Systems and Neural Networks · Physics 2015-05-19 Katharina Janzen , Andreas Engel

We introduce a hierarchical class of approximations of the random Ising spin glass in $d$ dimensions. The attention is focused on finite clusters of spins where the action of the rest of the system is properly taken into account. At the…

Disordered Systems and Neural Networks · Physics 2009-10-30 R. Baviera , M. Pasquini , M. Serva

Spin Glasses (SG) are paradigmatic models for physical, computer science, biological and social systems. The problem of studying the dynamics for SG models is NP hard, i.e., no algorithm solves it in polynomial time. Here we implement the…

Disordered Systems and Neural Networks · Physics 2021-07-14 M. Leonetti , E. Hörmann , L. Leuzzi , G. Parisi , G. Ruocco

We consider the problem of algorithmically sampling from the Gibbs measure of a mixed $p$-spin spherical spin glass. We give a polynomial-time algorithm that samples from the Gibbs measure up to vanishing total variation error, for any…

Probability · Mathematics 2024-04-25 Brice Huang , Andrea Montanari , Huy Tuan Pham

A full mean field solution of a quantum Heisenberg spin glass model is presented in a large-N limit. A spin glass transition is found for all values of the spin S. The quantum critical regime associated with the quantum transition at S=0,…

Disordered Systems and Neural Networks · Physics 2009-10-31 Antoine Georges , Olivier Parcollet , Subir Sachdev

The concept of replica symmetry breaking found in the solution of the mean-field Sherrington-Kirkpatrick spin-glass model has been applied to a variety of problems in science ranging from biological to computational and even financial…

Disordered Systems and Neural Networks · Physics 2008-03-25 Helmut G. Katzgraber , Alexander K. Hartmann , A. P. Young

We present a mean-field solution for a quantum, short-range interacting, disordered, SO(3) Heisenberg spin model, in which the Gaussian distribution of couplings is centered in an AF coupling $\bar J>0$, and which, for weak disorder, can be…

Disordered Systems and Neural Networks · Physics 2009-11-13 C. M. S. da Conceição , E. C. Marino

If the Boltzmann-Gibbs state $\omega_N$ of a mean-field $N$-particle system with Hamiltonian $H_N$ verifies the condition $$ \omega_N(H_N) \ge \omega_N(H_{N_1}+H_{N_2}) $$ for every decomposition $N_1+N_2=N$, then its free energy density…

Mathematical Physics · Physics 2007-05-23 A. Bianchi , P. Contucci , C. Giardina'

The Complexity of the Thouless-Anderson-Palmer (TAP) solutions of the Ising $p$-spin is investigated in the temperature regime where the equilibrium phase is one step Replica Symmetry Breaking. Two solutions of the resulting saddle point…

Statistical Mechanics · Physics 2016-08-31 A. Crisanti , L. Leuzzi , T. Rizzo

The central object of this PhD thesis is known under different names in the fields of computer science and statistical mechanics. In computer science, it is called the Maximum Cut problem, one of the famous twenty-one Karp's original…

Machine Learning · Computer Science 2022-08-31 Mikhail Krechetov
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