25 research outputs found
Generating droplets in two-dimensional Ising spin glasses by using matching algorithms
We study the behavior of droplets for two dimensional Ising spin glasses with
Gaussian interactions. We use an exact matching algorithm which enables study
of systems with linear dimension L up to 240, which is larger than is possible
with other approaches. But the method only allows certain classes of droplets
to be generated. We study single-bond, cross and a category of fixed volume
droplets as well as first excitations. By comparison with similar or equivalent
droplets generated in previous works, the advantages but also the limitations
of this approach are revealed. In particular we have studied the scaling
behavior of the droplet energies and droplet sizes. In most cases, a crossover
of the data can be observed such that for large sizes the behavior is
compatible with the one-exponent scenario of the droplet theory. Only for the
case of first excitations, no clear conclusion can be reached, probably because
even with the matching approach the accessible system sizes are still too
small.Comment: 11 pages, 16 figures, revte
Ground states of two-dimensional J Edwards-Anderson spin glasses
We present an exact algorithm for finding all the ground states of the
two-dimensional Edwards-Anderson spin glass and characterize its
performance. We investigate how the ground states change with increasing system
size and and with increasing antiferromagnetic bond ratio . We find that
that some system properties have very large and strongly non-Gaussian
variations between realizations.Comment: 15 pages, 21 figures, 2 tables, uses revtex4 macro
Ground-state behavior of the 3d +/-J random-bond Ising model
Large numbers of ground states of the three-dimensional random-bond
Ising model are calculated for sizes up to using a combination of a
genetic algorithm and Cluster-Exact Approximation. Several quantities are
calculated as function of the concentration of the antiferromagnetic bonds.
The critical concentration where the ferromagnetic order disappears is
determined using the Binder cumulant of the magnetization. A value of
is obtained. From the finite-size behavior of the Binder
cumulant and the magnetization critical exponents and
are calculated.Comment: 8 pages, 11 figures, revte
No spin-glass transition in the "mobile-bond" model
The recently introduced ``mobile-bond'' model for two-dimensional spin
glasses is studied. The model is characterized by an annealing temperature T_q.
On the basis of Monte Carlo simulations of small systems it has been claimed
that this model exhibits a non-trivial spin-glass transition at finite
temperature for small values of T_q.
Here the model is studied by means of exact ground-state calculations of
large systems up to N=256^2. The scaling of domain-wall energies is
investigated as a function of the system size. For small values T_q<0.95 the
system behaves like a (gauge-transformed) ferromagnet having a small fraction
of frustrated plaquettes. For T_q>=0.95 the system behaves like the standard
two-dimensional +-J spin-glass, i.e. it does NOT exhibit a phase transition at
T>0.Comment: 4 pages, 5 figures, RevTe
Einführung in die Wahrscheinlichkeitsrechnung. Bd. 1: Wahrscheinlichkeitsmaße und eindimensionale Zufallsgrößen
From recombination of genes to the estimation of distributions: II. Continuous parameters
. The Breeder Genetic Algorithm (BGA) is based on the equation for the response to selection. In order to use this equation for prediction, the variance of the fitness of the population has to be estimated. For the usual sexual recombination this can be difficult. In this paper the new points (offspring) are generated from distributions, a uniform distribution and a distribution generated by univariate marginal distributions. For a class of unimodal fitness functions the performance of the BGA is analytically computed. The results are compared to gene recombination methods. The uniform distribution is approximately generated by line recombination; recombination methods acting independently on each gene approximate the second distribution. 1 Introduction The Breeder Genetic Algorithm (BGA) is based on the classical science of livestock breeding. The central part of this theory is the equation for the response to selection R(t) = b(t) \Delta I \Delta oe(t) (1) Here R denotes the respon..
From recombination of genes to the estimation of distributions I. binary parameters
Abstract. The Breeder Genetic Algorithm (BGA) is based on the equation for the response to selection. In order to use this equation for prediction, the variance of the tness of the population has to be estimated. For the usual sexual recombination this can be di cult. In this paper the new points (o spring) are generated from distributions, a uniform distribution and a distribution generated by univariate marginal distributions. For a class of unimodal tness functions the performance of the BGA is analytically computed. The results are compared to gene recombination methods. The uniform distribution is approximately generated by line recombination � recombination methods acting independently on each gene approximate the second distribution.