81 research outputs found
Magnetic exponents of two-dimensional Ising spin glasses
The magnetic critical properties of two-dimensional Ising spin glasses are
controversial. Using exact ground state determination, we extract the
properties of clusters flipped when increasing continuously a uniform field. We
show that these clusters have many holes but otherwise have statistical
properties similar to those of zero-field droplets. A detailed analysis gives
for the magnetization exponent delta = 1.30 +/- 0.02 using lattice sizes up to
80x80; this is compatible with the droplet model prediction delta = 1.282. The
reason for previous disagreements stems from the need to analyze both singular
and analytic contributions in the low-field regime.Comment: 4 pages, 4 figures, title now includes "Ising
Zero-temperature behavior of the random-anisotropy model in the strong-anisotropy limit
We consider the random-anisotropy model on the square and on the cubic
lattice in the strong-anisotropy limit. We compute exact ground-state
configurations, and we use them to determine the stiffness exponent at zero
temperature; we find and respectively
in two and three dimensions. These results show that the low-temperature phase
of the model is the same as that of the usual Ising spin-glass model. We also
show that no magnetic order occurs in two dimensions, since the expectation
value of the magnetization is zero and spatial correlation functions decay
exponentially. In three dimensions our data strongly support the absence of
spontaneous magnetization in the infinite-volume limit
Exact Ground States of Large Two-Dimensional Planar Ising Spin Glasses
Studying spin-glass physics through analyzing their ground-state properties
has a long history. Although there exist polynomial-time algorithms for the
two-dimensional planar case, where the problem of finding ground states is
transformed to a minimum-weight perfect matching problem, the reachable system
sizes have been limited both by the needed CPU time and by memory requirements.
In this work, we present an algorithm for the calculation of exact ground
states for two-dimensional Ising spin glasses with free boundary conditions in
at least one direction. The algorithmic foundations of the method date back to
the work of Kasteleyn from the 1960s for computing the complete partition
function of the Ising model. Using Kasteleyn cities, we calculate exact ground
states for huge two-dimensional planar Ising spin-glass lattices (up to
3000x3000 spins) within reasonable time. According to our knowledge, these are
the largest sizes currently available. Kasteleyn cities were recently also used
by Thomas and Middleton in the context of extended ground states on the torus.
Moreover, they show that the method can also be used for computing ground
states of planar graphs. Furthermore, we point out that the correctness of
heuristically computed ground states can easily be verified. Finally, we
evaluate the solution quality of heuristic variants of the Bieche et al.
approach.Comment: 11 pages, 5 figures; shortened introduction, extended results; to
appear in Physical Review E 7
Matching Kasteleyn Cities for Spin Glass Ground States
As spin glass materials have extremely slow dynamics, devious numerical
methods are needed to study low-temperature states. A simple and fast
optimization version of the classical Kasteleyn treatment of the Ising model is
described and applied to two-dimensional Ising spin glasses. The algorithm
combines the Pfaffian and matching approaches to directly strip droplet
excitations from an excited state. Extended ground states in Ising spin glasses
on a torus, which are optimized over all boundary conditions, are used to
compute precise values for ground state energy densities.Comment: 4 pages, 2 figures; minor clarification
Negative-weight percolation
We describe a percolation problem on lattices (graphs, networks), with edge
weights drawn from disorder distributions that allow for weights (or distances)
of either sign, i.e. including negative weights. We are interested whether
there are spanning paths or loops of total negative weight. This kind of
percolation problem is fundamentally different from conventional percolation
problems, e.g. it does not exhibit transitivity, hence no simple definition of
clusters, and several spanning paths/loops might coexist in the percolation
regime at the same time. Furthermore, to study this percolation problem
numerically, one has to perform a non-trivial transformation of the original
graph and apply sophisticated matching algorithms.
Using this approach, we study the corresponding percolation transitions on
large square, hexagonal and cubic lattices for two types of disorder
distributions and determine the critical exponents. The results show that
negative-weight percolation is in a different universality class compared to
conventional bond/site percolation. On the other hand, negative-weight
percolation seems to be related to the ferromagnet/spin-glass transition of
random-bond Ising systems, at least in two dimensions.Comment: v1: 4 pages, 4 figures; v2: 10 pages, 7 figures, added results, text
and reference
Universality-class dependence of energy distributions in spin glasses
We study the probability distribution function of the ground-state energies
of the disordered one-dimensional Ising spin chain with power-law interactions
using a combination of parallel tempering Monte Carlo and branch, cut, and
price algorithms. By tuning the exponent of the power-law interactions we are
able to scan several universality classes. Our results suggest that mean-field
models have a non-Gaussian limiting distribution of the ground-state energies,
whereas non-mean-field models have a Gaussian limiting distribution. We compare
the results of the disordered one-dimensional Ising chain to results for a
disordered two-leg ladder, for which large system sizes can be studied, and
find a qualitative agreement between the disordered one-dimensional Ising chain
in the short-range universality class and the disordered two-leg ladder. We
show that the mean and the standard deviation of the ground-state energy
distributions scale with a power of the system size. In the mean-field
universality class the skewness does not follow a power-law behavior and
converges to a nonzero constant value. The data for the Sherrington-Kirkpatrick
model seem to be acceptably well fitted by a modified Gumbel distribution.
Finally, we discuss the distribution of the internal energy of the
Sherrington-Kirkpatrick model at finite temperatures and show that it behaves
similar to the ground-state energy of the system if the temperature is smaller
than the critical temperature.Comment: 15 pages, 20 figures, 1 tabl
Low Energy Excitations in Spin Glasses from Exact Ground States
We investigate the nature of the low-energy, large-scale excitations in the
three-dimensional Edwards-Anderson Ising spin glass with Gaussian couplings and
free boundary conditions, by studying the response of the ground state to a
coupling-dependent perturbation introduced previously. The ground states are
determined exactly for system sizes up to 12^3 spins using a branch and cut
algorithm. The data are consistent with a picture where the surface of the
excitations is not space-filling, such as the droplet or the ``TNT'' picture,
with only minimal corrections to scaling. When allowing for very large
corrections to scaling, the data are also consistent with a picture with
space-filling surfaces, such as replica symmetry breaking. The energy of the
excitations scales with their size with a small exponent \theta', which is
compatible with zero if we allow moderate corrections to scaling. We compare
the results with data for periodic boundary conditions obtained with a genetic
algorithm, and discuss the effects of different boundary conditions on
corrections to scaling. Finally, we analyze the performance of our branch and
cut algorithm, finding that it is correlated with the existence of
large-scale,low-energy excitations.Comment: 18 Revtex pages, 16 eps figures. Text significantly expanded with
more discussion of the numerical data. Fig.11 adde
Fixed Linear Crossing Minimization by Reduction to the Maximum Cut Problem
Many real-life scheduling, routing and locating problems can be formulated as combinatorial optimization problems whose goal is to find a linear layout of an input graph in such a way that the number of edge crossings is minimized. In this paper, we study a restricted version of the linear layout problem where the order of vertices on the line is fixed, the so-called fixed linear crossing number problem (FLCNP). We show that this NP-hard problem can be reduced to the well-known maximum cut problem. The latter problem was intensively studied in the literature; practically efficient exact algorithms based on the branch-and-cut technique have been developed. By an experimental evaluation on a variety of graphs, we prove that using this reduction for solving FLCNP compares favorably to earlier branch-and-bound algorithms
The ground state energy of the Edwards-Anderson spin glass model with a parallel tempering Monte Carlo algorithm
We study the efficiency of parallel tempering Monte Carlo technique for
calculating true ground states of the Edwards-Anderson spin glass model.
Bimodal and Gaussian bond distributions were considered in two and
three-dimensional lattices. By a systematic analysis we find a simple formula
to estimate the values of the parameters needed in the algorithm to find the GS
with a fixed average probability. We also study the performance of the
algorithm for single samples, quantifying the difference between samples where
the GS is hard, or easy, to find. The GS energies we obtain are in good
agreement with the values found in the literature. Our results show that the
performance of the parallel tempering technique is comparable to more powerful
heuristics developed to find the ground state of Ising spin glass systems.Comment: 30 pages, 17 figures. A new section added. Accepted for publication
in Physica
A Fixed-Parameter Algorithm for the Max-Cut Problem on Embedded 1-Planar Graphs
We propose a fixed-parameter tractable algorithm for the \textsc{Max-Cut}
problem on embedded 1-planar graphs parameterized by the crossing number of
the given embedding. A graph is called 1-planar if it can be drawn in the plane
with at most one crossing per edge. Our algorithm recursively reduces a
1-planar graph to at most planar graphs, using edge removal and node
contraction. The \textsc{Max-Cut} problem is then solved on the planar graphs
using established polynomial-time algorithms. We show that a maximum cut in the
given 1-planar graph can be derived from the solutions for the planar graphs.
Our algorithm computes a maximum cut in an embedded 1-planar graph with
nodes and edge crossings in time .Comment: conference version from IWOCA 201
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