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Although many efficient heuristics have been developed to solve binary optimization problems, these typically produce correlated solutions for degenerate problems. Most notably, transverse-field quantum annealing - the heuristic employed in…

Disordered Systems and Neural Networks · Physics 2019-06-27 Zheng Zhu , Andrew J. Ochoa , Helmut G. Katzgraber

In the presented article we present an algorithm for the computation of ground state spin configurations for the 2d random bond Ising model on planar triangular lattice graphs. Therefore, it is explained how the respective ground state…

Disordered Systems and Neural Networks · Physics 2015-05-19 O. Melchert , A. K. Hartmann

Systems with quenched disorder possess complex energy landscapes that are challenging to explore under the conventional Monte Carlo method. In this work, we implement an efficient entropy sampling scheme for accurate computation of the…

Disordered Systems and Neural Networks · Physics 2025-05-08 Yi Liu , Ding Wang , Xin Wang , Dao-Xin Yao , Lei-Han Tang

We present an algorithm for finding ground states of two dimensional spin glass systems based on ideas from matrix product states in quantum information theory. The algorithm works directly at zero temperature and defines an approximate…

Disordered Systems and Neural Networks · Physics 2009-11-13 M. B. Hastings

We present a collection of simulations of the Edwards-Anderson lattice spin glass at $T=0$ to elucidate the nature of low-energy excitations over a range of dimensions that reach from physically realizable systems to the mean-field limit.…

Disordered Systems and Neural Networks · Physics 2024-09-23 Stefan Boettcher

Large numbers of ground states of the three-dimensional $\pm J$ random-bond Ising model are calculated for sizes up to $14^3$ using a combination of a genetic algorithm and Cluster-Exact Approximation. Several quantities are calculated as…

Disordered Systems and Neural Networks · Physics 2009-10-31 Alexander K. Hartmann

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 study the performance of the D-Wave 2X quantum annealing machine on systems with well-controlled ground-state degeneracy. While obtaining the ground state of a spin-glass benchmark instance represents a difficult task, the gold standard…

Quantum Physics · Physics 2017-02-21 Salvatore Mandrà , Zheng Zhu , Helmut G. Katzgraber

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 compare the ground state of the random-field Ising model with Gaussian distributed random fields, with its non-equilibrium hysteretic counterpart, the demagnetized state. This is a low energy state obtained by a sequence of slow magnetic…

Computing the ground state of Ising spin-glass models with p-spin interactions is, in general, an NP-hard problem. In this work we show that unlike in the case of the standard Ising spin glass with two-spin interactions, computing ground…

Disordered Systems and Neural Networks · Physics 2015-03-17 Creighton K. Thomas , Helmut G. Katzgraber

The random field Ising model in three dimensions with Gaussian random fields is studied at zero temperature for system sizes up to 60^3. For each realization of the normalized random fields, the strength of the random field, Delta and a…

Statistical Mechanics · Physics 2009-11-07 Ilija Dukovski , Jon Machta

In this study the magnetization phenomenon has been investigated as a behavior of interacting elementary moments ensemble, with the help of Ising model [1] in the frame of non-extensive statistical mechanics. To investigate the physical…

Statistical Mechanics · Physics 2007-05-23 M. Karabekirogullari , F. Buyukkilic , D. Demirhan

Understanding extreme non-locality in many-body quantum systems can help resolve questions in thermostatistics and laser physics. The existence of symmetry selection rules for Hamiltonians with non-decaying terms on infinite-size lattices…

Strongly Correlated Electrons · Physics 2020-06-01 S. N. Saadatmand

For many real spin-glass materials, the Edwards-Anderson model with continuous-symmetry spins is more realistic than the rather better understood Ising variant. In principle, the nature of an occurring spin-glass phase in such systems might…

Disordered Systems and Neural Networks · Physics 2008-04-28 Martin Weigel , Michel J. P. Gingras

We investigate the performance of the recently proposed stationary Fokker-Planck sampling method considering a combinatorial optimization problem from statistical physics. The algorithmic procedure relies upon the numerical solution of a…

Disordered Systems and Neural Networks · Physics 2009-11-13 O. Melchert , A. K. Hartmann

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

The ground-state properties of quasi-one-dimensional (Q1D) Ising spin glass are investigated using an exact numerical approach and analytical arguments. A set of coupled recursive equations for the ground-state energy are introduced and…

Disordered Systems and Neural Networks · Physics 2018-03-28 Reza Sepehrinia , Fartash Chalangari

A method is presented, which allows to sample directly low-temperature configurations of glassy systems, like spin glasses. The basic idea is to generate ground states and low lying excited configurations using a heuristic algorithm. Then,…

Disordered Systems and Neural Networks · Physics 2009-11-07 Alexander K. Hartmann , Federico Ricci-Tersenghi

The nature of the zero temperature ordering transition in the 3D Gaussian random field Ising magnet is studied numerically, aided by scaling analyses. In the ferromagnetic phase the scaling of the roughness of the domain walls, $w\sim…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. Alan Middleton , Daniel S. Fisher
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