658 research outputs found
Specific Heat Exponent for the 3-d Ising Model from a 24-th Order High Temperature Series
We compute high temperature expansions of the 3-d Ising model using a
recursive transfer-matrix algorithm and extend the expansion of the free energy
to 24th order. Using ID-Pade and ratio methods, we extract the critical
exponent of the specific heat to be alpha=0.104(4).Comment: 10 pages, LaTeX with 5 eps-figures using epsf.sty, IASSNS-93/83 and
WUB-93-4
Series expansions without diagrams
We discuss the use of recursive enumeration schemes to obtain low and high
temperature series expansions for discrete statistical systems. Using linear
combinations of generalized helical lattices, the method is competitive with
diagramatic approaches and is easily generalizable. We illustrate the approach
using the Ising model and generate low temperature series in up to five
dimensions and high temperature series in three dimensions. The method is
general and can be applied to any discrete model. We describe how it would work
for Potts models.Comment: 24 pages, IASSNS-HEP-93/1
Large Nc Continuum Reduction and the Thermodynamics of QCD
It is noted that if large Nc continuum reduction applies to an observable,
then that observable is independent of temperature for all temperatures below
some critical value. This fact, plus the fact that mesons and glueballs are
weakly interacting at large Nc is used as the basis for a derivation of large
Nc continuum reduction for the chiral condensate. The structure of this
derivation is quite general and can be extended to a wide class of observables
Critical behaviour of SU(2) lattice gauge theory. A complete analysis with the -method
We determine the critical point and the ratios and
of critical exponents of the deconfinement transition in gauge theory
by applying the -method to Monte Carlo data of the modulus and the
square of the Polyakov loop. With the same technique we find from the Binder
cumulant its universal value at the critical point in the thermodynamical
limit to and for the next-to-leading exponent .
From the derivatives of the Polyakov loop dependent quantities we estimate then
. The result from the derivative of is , in
complete agreement with that of the Ising model.Comment: 11 pages, 3 Postscript figures, uses Plain Te
Low temperature expansion for the 3-d Ising Model
We compute the weak coupling expansion for the energy of the three
dimensional Ising model through 48 excited bonds. We also compute the
magnetization through 40 excited bonds. This was achieved via a recursive
enumeration of states of fixed energy on a set of finite lattices. We use a
linear combination of lattices with a generalization of helical boundary
conditions to eliminate finite volume effects.Comment: 10 pages, IASSNS-HEP-92/42, BNL-4767
New Algorithm of the Finite Lattice Method for the High-temperature Expansion of the Ising Model in Three Dimensions
We propose a new algorithm of the finite lattice method to generate the
high-temperature series for the Ising model in three dimensions. It enables us
to extend the series for the free energy of the simple cubic lattice from the
previous series of 26th order to 46th order in the inverse temperature. The
obtained series give the estimate of the critical exponent for the specific
heat in high precision.Comment: 4 pages, 4 figures, submitted to Phys. Rev. Letter
A Noisy Monte Carlo Algorithm
We propose a Monte Carlo algorithm to promote Kennedy and Kuti's linear
accept/reject algorithm which accommodates unbiased stochastic estimates of the
probability to an exact one. This is achieved by adopting the Metropolis
accept/reject steps for both the dynamical and noise configurations. We test it
on the five state model and obtain desirable results even for the case with
large noise. We also discuss its application to lattice QCD with stochastically
estimated fermion determinants.Comment: 10 pages, 1 tabl
Breakdown of large-N quenched reduction in SU(N) lattice gauge theories
We study the validity of the large-N equivalence between four-dimensional
SU(N) lattice gauge theory and its momentum quenched version--the Quenched
Eguchi-Kawai (QEK) model. We find that the assumptions needed for the proofs of
equivalence do not automatically follow from the quenching prescription. We use
weak-coupling arguments to show that large-N equivalence is in fact likely to
break down in the QEK model, and that this is due to dynamically generated
correlations between different Euclidean components of the gauge fields. We
then use Monte-Carlo simulations at intermediate couplings with 20 <= N <= 200
to provide strong evidence for the presence of these correlations and for the
consequent breakdown of reduction. This evidence includes a large discrepancy
between the transition coupling of the "bulk" transition in lattice gauge
theories and the coupling at which the QEK model goes through a strongly
first-order transition. To accurately measure this discrepancy we adapt the
recently introduced Wang-Landau algorithm to gauge theories.Comment: 51 pages, 16 figures, Published verion. Historical inaccuracies in
the review of the quenched Eguchi-Kawai model are corrected, discussion on
reduction at strong-coupling added, references updated, typos corrected. No
changes to results or conclusion
Data Perturbation Independent Diagnosis and Validation of Breast Cancer Subtypes Using Clustering and Patterns
Molecular stratification of disease based on expression levels of sets of genes can help guide therapeutic decisions if such classifications can be shown to be stable against variations in sample source and data perturbation. Classifications inferred from one set of samples in one lab should be able to consistently stratify a different set of samples in another lab. We present a method for assessing such stability and apply it to the breast cancer (BCA) datasets of Sorlie et al. 2003 and Ma et al. 2003. We find that within the now commonly accepted BCA categories identified by Sorlie et al. Luminal A and Basal are robust, but Luminal B and ERBB2+ are not. In particular, 36% of the samples identified as Luminal B and 55% identified as ERBB2+ cannot be assigned an accurate category because the classification is sensitive to data perturbation. We identify a “core cluster” of samples for each category, and from these we determine “patterns” of gene expression that distinguish the core clusters from each other. We find that the best markers for Luminal A and Basal are (ESR1, LIV1, GATA-3) and (CCNE1, LAD1, KRT5), respectively. Pathways enriched in the patterns regulate apoptosis, tissue remodeling and the immune response. We use a different dataset (Ma et al. 2003) to test the accuracy with which samples can be allocated to the four disease subtypes. We find, as expected, that the classification of samples identified as Luminal A and Basal is robust but classification into the other two subtypes is not
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