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The average ground state energies for spin glasses on Bethe lattices of connectivities r=3,...,15 are studied numerically for a Gaussian bond distribution. The Extremal Optimization heuristic is employed which provides high-quality…

Disordered Systems and Neural Networks · Physics 2010-04-13 S. Boettcher

We present a numerical study of ground states of the dilute versions of the Sherrington-Kirkpatrick (SK) mean-field spin glass. In contrast to so-called "sparse" mean-field spin glasses that have been studied widely on random networks of…

Disordered Systems and Neural Networks · Physics 2022-04-21 Stefan Boettcher

The average ground state energy and entropy for +/- J spin glasses on Bethe lattices of connectivities k+1=3...,26 at T=0 are approximated numerically. To obtain sufficient accuracy for large system sizes (up to n=2048), the Extremal…

Disordered Systems and Neural Networks · Physics 2022-05-20 S. Boettcher

We compare the performance of extremal optimization (EO), flat-histogram and equal-hit algorithms for finding spin-glass ground states. The first-passage-times to a ground state are computed. At optimal parameter of tau=1.15, EO outperforms…

Statistical Mechanics · Physics 2009-11-07 Jian-Sheng Wang , Yutaka Okabe

This study focuses on the problem of finding ground states of random instances of the Sherrington-Kirkpatrick (SK) spin-glass model with Gaussian couplings. While the ground states of SK spin-glass instances can be obtained with branch and…

Disordered Systems and Neural Networks · Physics 2009-07-29 Martin Pelikan , Helmut G. Katzgraber , Sigismund Kobe

We use heuristic optimization methods in extensive computations to determine with low systematic error ground state configurations of the mean-field $p$-spin glass model with $p=3$. Here, all possible triplets in a system of $N$ Ising spins…

Disordered Systems and Neural Networks · Physics 2025-08-27 Stefan Boettcher , Ginger E. Lau

We analyze the transformation of QUBO from its conventional Boolean presentation into an equivalent spin glass problem with coupled $\pm1$ spin variables exposed to a site-dependent external field. We find that in a widely used testbed for…

Disordered Systems and Neural Networks · Physics 2022-04-21 Stefan Boettcher

A version of the extremal optimization (EO) algorithm introduced by Boettcher and Percus is tested on 2D and 3D spin glasses with Gaussian disorder. EO preferentially flips spins that are locally ``unfit''; the variant introduced here…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. Alan Middleton

Hysteretic optimization is a heuristic optimization method based on the observation that magnetic samples are driven into a low energy state when demagnetized by an oscillating magnetic field of decreasing amplitude. We show that hysteretic…

Disordered Systems and Neural Networks · Physics 2009-11-11 Karoly F. Pal

Using a stochastic algorithm introduced in a previous paper, we study the finite size volume corrections and the fluctuations of the ground state energy in the Sherrington-Kirkpatrick and the Edwards-Anderson models at zero temperature. The…

Disordered Systems and Neural Networks · Physics 2008-07-09 Claudio Giberti , Cecilia Vernia

Using the discrete $\pm J$ bond distribution for the Sherrington-Kirkpatrick spin glass, all ground states for the entire ensemble of the bond disorder are enumerated. Although the combinatorial complexity of the enumeration severely…

Disordered Systems and Neural Networks · Physics 2007-05-23 Stefan Boettcher , Tomasz M. Kott

Ground states of Ising spin glasses on fully connected graphs are studied for a broadly distributed bond family. In particular, bonds $J$ distributed according to a Levy distribution P(J)\propto 1/|J|^{1+\alpha}, |J|>1, are investigated for…

Disordered Systems and Neural Networks · Physics 2014-11-25 S. Boettcher

The scaling of fluctuations in the distribution of ground-state energies or costs with the system size N for Ising spin glasses is considered using an extensive set of simulations with the Extremal Optimization heuristic across a range of…

Disordered Systems and Neural Networks · Physics 2022-05-20 Stefan Boettcher

Using a non-thermal local search, called Extremal Optimization (EO), in conjunction with a recently developed scheme for classifying the valley structure of complex systems, we analyze a short-range spin glass. In comparison with earlier…

Disordered Systems and Neural Networks · Physics 2009-11-10 Stefan Boettcher , Paolo Sibani

The recently proposed Hysteretic Optimization (HO) procedure is applied to the 1D Ising spin chain with long range interactions. To study its effectiveness, the quality of ground state energies found as a function of the distance dependence…

Soft Condensed Matter · Physics 2008-01-30 B. Goncalves , S. Boettcher

The probability distribution function (PDF) of the ground-state energy in the Sherrington-Kirkpatrick spin-glass model is numerically determined by collecting a large statistical sample of ground states, computed using a genetic algorithm.…

Disordered Systems and Neural Networks · Physics 2007-05-23 Matteo Palassini

Exact ground states are calculated for the Sherrington-Kirkpatrick (SK) spin-glass containing up to N=90 spins. A ground-state energy per spin $e^{\infty}_0 = - 0.7637 \pm 0.0004$ is found from the $N$ dependence of the misfit parameter,…

Disordered Systems and Neural Networks · Physics 2007-05-23 S. Kobe

Due to an extremely rugged structure of the free energy landscape, the determination of spin-glass ground states is among the hardest known optimization problems, found to be NP-hard in the most general case. Owing to the specific structure…

Disordered Systems and Neural Networks · Physics 2011-11-10 Martin Weigel

We explore a new general-purpose heuristic for finding high-quality solutions to hard optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent…

Statistical Mechanics · Physics 2009-10-31 S. Boettcher , A. G. Percus

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
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