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Related papers: Number partitioning as random energy model

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The sample-to-sample fluctuations of the free energy in finite-dimensional Ising spin glasses are calculated, using the replica method, from higher order terms in the replica number $n$. It is shown that the Parisi symmetry breaking scheme…

Statistical Mechanics · Physics 2009-11-07 T. Aspelmeier , M. A. Moore

We consider the problem of rational decision making in the presence of nonlinear constraints. By using tools borrowed from spin glass and random matrix theory, we focus on the portfolio optimisation problem. We show that the number of…

Disordered Systems and Neural Networks · Physics 2015-06-25 Stefano Galluccio , Jean-Philippe Bouchaud , Marc Potters

We study a family of inhomogeneous Ising chain models along with an equivalent family of nearest neighbour particle systems. By the correspondence between the two families we prove identities of combinatorial significance relating to…

Probability · Mathematics 2024-01-30 Jessica Jay , Benjamin Lees

We derive an exact path integral formulation for the partition function for the Ising model using a mapping between spins and poles of a Laurent expansion for a field on the complex plane. The advantage in using this formulation for the…

Statistical Mechanics · Physics 2019-08-23 Francesco Caravelli

In an earlier work, the statistical physics associated with finite--temperature decoding of code ensembles, along with the relation to their random coding error exponents, were explored in a framework that is analogous to Derrida's random…

Information Theory · Computer Science 2016-11-15 Neri Merhav

We propose a general learning algorithm for solving optimization problems, based on a simple strategy of trial and adaptation. The algorithm maintains a probability distribution of possible solutions (configurations), which is updated…

adap-org · Physics 2009-10-30 Kan Chen

We introduce the notion of a restricted exchangeable partition of $\mathbb{N}$. We obtain integral representations, consider associated fragmentations, embeddings into continuum random trees and convergence to such limit trees. In…

Probability · Mathematics 2012-11-12 Bo Chen , Matthias Winkel

The paper presents complexity results and performance guaranties for a family of approximation algorithms for an optimisation problem arising in software testing and manufacturing. The problem is formulated as a partitioning of a set where…

Data Structures and Algorithms · Computer Science 2022-12-13 Yakov Zinder , Bertrand M. T. Lin , Joanna Berlińska

We consider a class of particle systems which appear in various applications such as approximation theory, plasticity, potential theory and space-filling designs. The positions of the particles on the real line are described as a global…

Analysis of PDEs · Mathematics 2022-10-05 Patrick van Meurs , Ken'ichiro Tanaka

The usual interaction energy of the random field Ising model in statistical physics is modified by complementing the random field by added to the energy of the usual Ising model a nonlinear term S^n were S is the sum of the neighbor spins,…

Computational Physics · Physics 2011-06-29 M. A. Sumour , M. A. Radwan , M. M. Shabat

We present a method to show that low-energy states of quantum many-body interacting systems in one spatial dimension are nonlocal. We assign a Bell inequality to the Hamiltonian of the system in a natural way and we efficiently find its…

Among various algorithms designed to exploit the specific properties of quantum computers with respect to classical ones, the quantum adiabatic algorithm is a versatile proposition to find the minimal value of an arbitrary cost function…

Statistical Mechanics · Physics 2013-01-29 Victor Bapst , Laura Foini , Florent Krzakala , Guilhem Semerjian , Francesco Zamponi

This paper is about how to partition decision variables while decomposing a large-scale optimization problem for the best performance of distributed solution methods. Solving a large-scale optimization problem sequen- tially can be…

Optimization and Control · Mathematics 2017-10-26 Yuchen Zheng , Ilbin Lee , Nicoleta Serban

We consider the problem of estimating the maximal energy of quantum $p$-local spin glass random Hamiltonians, the quantum analogues of widely studied classical spin glass models. Denoting by $E^*(p)$ the (appropriately normalized) maximal…

Quantum Physics · Physics 2024-04-08 Eric R. Anschuetz , David Gamarnik , Bobak T. Kiani

Exploiting quantum properties to outperform classical ways of information-processing is an outstanding goal of modern physics. A promising route is quantum simulation, which aims at implementing relevant and computationally hard problems in…

For a set of nonnegative integers $S$ let $R_{S}(n)$ denote the number of unordered representations of the integer $n$ as the sum of two different terms from $S$. In this paper we focus on partitions of the natural numbers into two sets…

Number Theory · Mathematics 2016-08-22 Sándor Z. Kiss , Csaba Sándor

An analysis of the dynamics is performed, of exactly solvable models for fragile and strong glasses, exploiting the partitioning of the free energy landscape in inherent structures. The results are compared with the exact solution of the…

Statistical Mechanics · Physics 2009-11-07 Luca Leuzzi , Theo M. Nieuwenhuizen

We consider the ability of local quantum dynamics to solve the energy matching problem: given an instance of a classical optimization problem and a low energy state, find another macroscopically distinct low energy state. Energy matching is…

Disordered Systems and Neural Networks · Physics 2018-06-20 C. L. Baldwin , C. R. Laumann

Motivated by a geometric problem, we introduce a new non-convex graph partitioning objective where the optimality criterion is given by the sum of the Dirichlet eigenvalues of the partition components. A relaxed formulation is identified…

Optimization and Control · Mathematics 2016-03-29 Braxton Osting , Chris D. White , Edouard Oudet

In this thesis I discuss combinatorial optimization problems, from the statistical physics perspective. The starting point are the motivations which brought physicists together with computer scientists and mathematicians to work on this…

Disordered Systems and Neural Networks · Physics 2020-01-13 Andrea Di Gioacchino