2,150 research outputs found
Growth models, random matrices and Painleve transcendents
The Hammersley process relates to the statistical properties of the maximum
length of all up/right paths connecting random points of a given density in the
unit square from (0,0) to (1,1). This process can also be interpreted in terms
of the height of the polynuclear growth model, or the length of the longest
increasing subsequence in a random permutation. The cumulative distribution of
the longest path length can be written in terms of an average over the unitary
group. Versions of the Hammersley process in which the points are constrained
to have certain symmetries of the square allow similar formulas. The derivation
of these formulas is reviewed. Generalizing the original model to have point
sources along two boundaries of the square, and appropriately scaling the
parameters gives a model in the KPZ universality class. Following works of Baik
and Rains, and Pr\"ahofer and Spohn, we review the calculation of the scaled
cumulative distribution, in which a particular Painlev\'e II transcendent plays
a prominent role.Comment: 27 pages, 5 figure
Increasing subsequences and the hard-to-soft edge transition in matrix ensembles
Our interest is in the cumulative probabilities Pr(L(t) \le l) for the
maximum length of increasing subsequences in Poissonized ensembles of random
permutations, random fixed point free involutions and reversed random fixed
point free involutions. It is shown that these probabilities are equal to the
hard edge gap probability for matrix ensembles with unitary, orthogonal and
symplectic symmetry respectively. The gap probabilities can be written as a sum
over correlations for certain determinantal point processes. From these
expressions a proof can be given that the limiting form of Pr(L(t) \le l) in
the three cases is equal to the soft edge gap probability for matrix ensembles
with unitary, orthogonal and symplectic symmetry respectively, thereby
reclaiming theorems due to Baik-Deift-Johansson and Baik-Rains.Comment: LaTeX, 19 page
Scaling limit of vicious walks and two-matrix model
We consider the diffusion scaling limit of the one-dimensional vicious walker
model of Fisher and derive a system of nonintersecting Brownian motions. The
spatial distribution of particles is studied and it is described by use of
the probability density function of eigenvalues of Gaussian random
matrices. The particle distribution depends on the ratio of the observation
time and the time interval in which the nonintersecting condition is
imposed. As is going on from 0 to 1, there occurs a transition of
distribution, which is identified with the transition observed in the
two-matrix model of Pandey and Mehta. Despite of the absence of matrix
structure in the original vicious walker model, in the diffusion scaling limit,
accumulation of contact repulsive interactions realizes the correlated
distribution of eigenvalues in the multimatrix model as the particle
distribution.Comment: REVTeX4, 12 pages, no figure, minor corrections made for publicatio
The plasma picture of the fractional quantum Hall effect with internal SU(K) symmetries
We consider trial wavefunctions exhibiting SU(K) symmetry which may be
well-suited to grasp the physics of the fractional quantum Hall effect with
internal degrees of freedom. Systems of relevance may be either
spin-unpolarized states (K=2), semiconductors bilayers (K=2,4) or graphene
(K=4). We find that some introduced states are unstable, undergoing phase
separation or phase transition. This allows us to strongly reduce the set of
candidate wavefunctions eligible for a particular filling factor. The stability
criteria are obtained with the help of Laughlin's plasma analogy, which we
systematically generalize to the multicomponent SU(K) case. The validity of
these criteria are corroborated by exact-diagonalization studies, for SU(2) and
SU(4). Furthermore, we study the pair-correlation functions of the ground state
and elementary charged excitations within the multicomponent plasma picture.Comment: 13 pages, 7 figures; reference added, accepted for publication in PR
Eigenvalue Separation in Some Random Matrix Models
The eigenvalue density for members of the Gaussian orthogonal and unitary
ensembles follows the Wigner semi-circle law. If the Gaussian entries are all
shifted by a constant amount c/Sqrt(2N), where N is the size of the matrix, in
the large N limit a single eigenvalue will separate from the support of the
Wigner semi-circle provided c > 1. In this study, using an asymptotic analysis
of the secular equation for the eigenvalue condition, we compare this effect to
analogous effects occurring in general variance Wishart matrices and matrices
from the shifted mean chiral ensemble. We undertake an analogous comparative
study of eigenvalue separation properties when the size of the matrices are
fixed and c goes to infinity, and higher rank analogues of this setting. This
is done using exact expressions for eigenvalue probability densities in terms
of generalized hypergeometric functions, and using the interpretation of the
latter as a Green function in the Dyson Brownian motion model. For the shifted
mean Gaussian unitary ensemble and its analogues an alternative approach is to
use exact expressions for the correlation functions in terms of classical
orthogonal polynomials and associated multiple generalizations. By using these
exact expressions to compute and plot the eigenvalue density, illustrations of
the various eigenvalue separation effects are obtained.Comment: 25 pages, 9 figures include
Variance Calculations and the Bessel Kernel
In the Laguerre ensemble of N x N (positive) hermitian matrices, it is of
interest both theoretically and for applications to quantum transport problems
to compute the variance of a linear statistic, denoted var_N f, as N->infinity.
Furthermore, this statistic often contains an additional parameter alpha for
which the limit alpha->infinity is most interesting and most difficult to
compute numerically. We derive exact expressions for both lim_{N->infinity}
var_N f and lim_{alpha->infinity}lim_{N->infinity} var_N f.Comment: 7 pages; resubmitted to make postscript compatibl
The Partition Function of Multicomponent Log-Gases
We give an expression for the partition function of a one-dimensional log-gas
comprised of particles of (possibly) different integer charge at inverse
temperature {\beta} = 1 (restricted to the line in the presence of a
neutralizing field) in terms of the Berezin integral of an associated non-
homogeneous alternating tensor. This is the analog of the de Bruijn integral
identities [3] (for {\beta} = 1 and {\beta} = 4) ensembles extended to
multicomponent ensembles.Comment: 14 page
Designing Effective Habitat Studies: Quantifying Multiple Sources of Variability in Bat Activity
Common aims of habitat studies are to differentiate between (i) suitable and unsuitable sites for a given species, and (ii) sites used by different communities of species. To quantify differences between sites, field data of site use must be precise enough that true underlying between-site variability is not masked by within-site measurement error. We designed a pilot study to guide the development of a survey protocol for a habitat study on bats in an agricultural landscape in southeastern Australia. Three woodland sites and two scattered tree sites of 2 ha each were surveyed for nine consecutive nights. At three locations within each site (spaced > 50 m apart) one or two Anabat detectors were mounted 1 m above ground or in a tree (2 m above ground). We used mixed regression models to quantify multiple sources of variability in bat calling activity, and graphical data analysis to visualise how increases in survey effort were likely to affect inference. For the five most active species, we found that typically over 40% of variability in nightly detections occurred at the between-site level; approximately 10% occurred between locations within sites; approximately 20% was explained by night-to-night differences; and approximately 30% of variability was not attributable to systematic variation within experimental units. Differences in community composition between sites were clearly evident when two or more detectors per site were used for four or more nights. We conclude with six general considerations for the design of effective habitat studies. These are to (i) consider key contrasts of interest; (ii) use data from mild, calm, dry nights only; (iii) calibrate detectors; (iv) use multiple detectors where possible, or move a single detector within a site; (v) survey for multiple nights; and (vi) where vertical differentiation in habitat use is likely, mount detectors at different heights. These considerations need to be balanced within the context of financial and logistical constraints
Exact Dynamical Correlation Functions of Calogero-Sutherland Model and One-Dimensional Fractional Statistics
One-dimensional model of non-relativistic particles with inverse-square
interaction potential known as Calogero-Sutherland Model (CSM) is shown to
possess fractional statistics. Using the theory of Jack symmetric polynomial
the exact dynamical density-density correlation function and the one-particle
Green's function (hole propagator) at any rational interaction coupling
constant are obtained and used to show clear evidences of the
fractional statistics. Motifs representing the eigenstates of the model are
also constructed and used to reveal the fractional {\it exclusion} statistics
(in the sense of Haldane's ``Generalized Pauli Exclusion Principle''). This
model is also endowed with a natural {\it exchange } statistics (1D analog of
2D braiding statistics) compatible with the {\it exclusion} statistics.
(Submitted to PRL on April 18, 1994)Comment: Revtex 11 pages, IASSNS-HEP-94/27 (April 18, 1994
From Random Matrices to Stochastic Operators
We propose that classical random matrix models are properly viewed as finite
difference schemes for stochastic differential operators. Three particular
stochastic operators commonly arise, each associated with a familiar class of
local eigenvalue behavior. The stochastic Airy operator displays soft edge
behavior, associated with the Airy kernel. The stochastic Bessel operator
displays hard edge behavior, associated with the Bessel kernel. The article
concludes with suggestions for a stochastic sine operator, which would display
bulk behavior, associated with the sine kernel.Comment: 41 pages, 5 figures. Submitted to Journal of Statistical Physics.
Changes in this revision: recomputed Monte Carlo simulations, added reference
[19], fit into margins, performed minor editin
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