47 research outputs found
A dedicated algorithm for calculating ground states for the triangular random bond Ising model
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 problem can be mapped to an auxiliary minimum-weight perfect matching
problem, solvable in polynomial time. Consequently, the ground state properties
as well as minimum-energy domain wall (MEDW) excitations for very large 2d
systems, e.g. lattice graphs with up to N=384x384 spins, can be analyzed very
fast. Here, we investigate the critical behavior of the corresponding T=0
ferromagnet to spin-glass transition, signaled by a breakdown of the
magnetization, using finite-size scaling analyses of the magnetization and MEDW
excitation energy and we contrast our numerical results with previous
simulations and presumably exact results.Comment: 5 pages, 5 figure
Near optimal configurations in mean field disordered systems
We present a general technique to compute how the energy of a configuration
varies as a function of its overlap with the ground state in the case of
optimization problems. Our approach is based on a generalization of the cavity
method to a system interacting with its ground state. With this technique we
study the random matching problem as well as the mean field diluted spin glass.
As a byproduct of this approach we calculate the de Almeida-Thouless transition
line of the spin glass on a fixed connectivity random graph.Comment: 13 pages, 7 figure
Optimal Approximation Algorithms for Multi-agent Combinatorial Problems with Discounted Price Functions
Submodular functions are an important class of functions in combinatorial
optimization which satisfy the natural properties of decreasing marginal costs.
The study of these functions has led to strong structural properties with
applications in many areas. Recently, there has been significant interest in
extending the theory of algorithms for optimizing combinatorial problems (such
as network design problem of spanning tree) over submodular functions.
Unfortunately, the lower bounds under the general class of submodular functions
are known to be very high for many of the classical problems.
In this paper, we introduce and study an important subclass of submodular
functions, which we call discounted price functions. These functions are
succinctly representable and generalize linear cost functions. In this paper we
study the following fundamental combinatorial optimization problems: Edge
Cover, Spanning Tree, Perfect Matching and Shortest Path, and obtain tight
upper and lower bounds for these problems.
The main technical contribution of this paper is designing novel adaptive
greedy algorithms for the above problems. These algorithms greedily build the
solution whist rectifying mistakes made in the previous steps
Solving a "Hard" Problem to Approximate an "Easy" One: Heuristics for Maximum Matchings and Maximum Traveling Salesman Problems
We consider geometric instances of the Maximum Weighted Matching Problem
(MWMP) and the Maximum Traveling Salesman Problem (MTSP) with up to 3,000,000
vertices. Making use of a geometric duality relationship between MWMP, MTSP,
and the Fermat-Weber-Problem (FWP), we develop a heuristic approach that yields
in near-linear time solutions as well as upper bounds. Using various
computational tools, we get solutions within considerably less than 1% of the
optimum.
An interesting feature of our approach is that, even though an FWP is hard to
compute in theory and Edmonds' algorithm for maximum weighted matching yields a
polynomial solution for the MWMP, the practical behavior is just the opposite,
and we can solve the FWP with high accuracy in order to find a good heuristic
solution for the MWMP.Comment: 20 pages, 14 figures, Latex, to appear in Journal of Experimental
Algorithms, 200
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
Error-free milestones in error prone measurements
A predictor variable or dose that is measured with substantial error may
possess an error-free milestone, such that it is known with negligible error
whether the value of the variable is to the left or right of the milestone.
Such a milestone provides a basis for estimating a linear relationship between
the true but unknown value of the error-free predictor and an outcome, because
the milestone creates a strong and valid instrumental variable. The inferences
are nonparametric and robust, and in the simplest cases, they are exact and
distribution free. We also consider multiple milestones for a single predictor
and milestones for several predictors whose partial slopes are estimated
simultaneously. Examples are drawn from the Wisconsin Longitudinal Study, in
which a BA degree acts as a milestone for sixteen years of education, and the
binary indicator of military service acts as a milestone for years of service.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS233 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Designing q-Unique DNA Sequences with Integer Linear Programs and Euler Tours in De Bruijn Graphs
DNA nanoarchitechtures require carefully designed oligonucleotides with certain non-hybridization guarantees, which can be formalized as the q-uniqueness property on the sequence level. We study the optimization problem of finding a longest q-unique DNA sequence. We first present a convenient formulation as an integer linear program on the underlying De Bruijn graph that allows to flexibly incorporate a variety of constraints; solution times for practically relevant values of q are short. We then provide additional insights into the problem structure using the quotient graph of the De Bruijn graph with respect to the equivalence relation induced by reverse complementarity. Specifically, for odd q the quotient graph is Eulerian, so finding a longest q-unique sequence is equivalent to finding an Euler tour and solved in linear time with respect to the output string length. For even q, self-complementary edges complicate the problem, and the graph has to be Eulerized by deleting a minimum number of edges. Two sub-cases arise, for one of which we present a complete solution, while the other one remains open