1,207 research outputs found
Dynamics of a tagged particle in the asymmetric exclusion process with the step initial condition
The one-dimensional totally asymmetric simple exclusion process (TASEP) is
considered. We study the time evolution property of a tagged particle in TASEP
with the step-type initial condition. Calculated is the multi-time joint
distribution function of its position. Using the relation of the dynamics of
TASEP to the Schur process, we show that the function is represented as the
Fredholm determinant. We also study the scaling limit. The universality of the
largest eigenvalue in the random matrix theory is realized in the limit. When
the hopping rates of all particles are the same, it is found that the joint
distribution function converges to that of the Airy process after the time at
which the particle begins to move. On the other hand, when there are several
particles with small hopping rate in front of a tagged particle, the limiting
process changes at a certain time from the Airy process to the process of the
largest eigenvalue in the Hermitian multi-matrix model with external sources.Comment: 48 pages, 8 figure
Edge scaling limits for a family of non-Hermitian random matrix ensembles
A family of random matrix ensembles interpolating between the GUE and the
Ginibre ensemble of matrices with iid centered complex Gaussian
entries is considered. The asymptotic spectral distribution in these models is
uniform in an ellipse in the complex plane, which collapses to an interval of
the real line as the degree of non-Hermiticity diminishes. Scaling limit
theorems are proven for the eigenvalue point process at the rightmost edge of
the spectrum, and it is shown that a non-trivial transition occurs between
Poisson and Airy point process statistics when the ratio of the axes of the
supporting ellipse is of order . In this regime, the family of
limiting probability distributions of the maximum of the real parts of the
eigenvalues interpolates between the Gumbel and Tracy-Widom distributions.Comment: 44 page
Expected length of the longest common subsequence for large alphabets
We consider the length L of the longest common subsequence of two randomly
uniformly and independently chosen n character words over a k-ary alphabet.
Subadditivity arguments yield that the expected value of L, when normalized by
n, converges to a constant C_k. We prove a conjecture of Sankoff and Mainville
from the early 80's claiming that C_k\sqrt{k} goes to 2 as k goes to infinity.Comment: 14 pages, 1 figure, LaTe
On the partial connection between random matrices and interacting particle systems
In the last decade there has been increasing interest in the fields of random
matrices, interacting particle systems, stochastic growth models, and the
connections between these areas. For instance, several objects appearing in the
limit of large matrices arise also in the long time limit for interacting
particles and growth models. Examples of these are the famous Tracy-Widom
distribution functions and the Airy_2 process. The link is however sometimes
fragile. For example, the connection between the eigenvalues in the Gaussian
Orthogonal Ensembles (GOE) and growth on a flat substrate is restricted to
one-point distribution, and the connection breaks down if we consider the joint
distributions. In this paper we first discuss known relations between random
matrices and the asymmetric exclusion process (and a 2+1 dimensional
extension). Then, we show that the correlation functions of the eigenvalues of
the matrix minors for beta=2 Dyson's Brownian motion have, when restricted to
increasing times and decreasing matrix dimensions, the same correlation kernel
as in the 2+1 dimensional interacting particle system under diffusion scaling
limit. Finally, we analyze the analogous question for a diffusion on (complex)
sample covariance matrices.Comment: 31 pages, LaTeX; Added a section concerning the Markov property on
space-like path
Replica field theories, Painleve transcendents, and exact correlation functions
Exact solvability is claimed for nonlinear replica sigma models derived in
the context of random matrix theories. Contrary to other approaches reported in
the literature, the framework outlined does not rely on traditional "replica
symmetry breaking" but rests on a previously unnoticed exact relation between
replica partition functions and Painleve transcendents. While expected to be
applicable to matrix models of arbitrary symmetries, the method is used to
treat fermionic replicas for the Gaussian unitary ensemble (GUE), chiral GUE
(symmetry classes A and AIII in Cartan classification) and Ginibre's ensemble
of complex non-Hermitean random matrices. Further applications are briefly
discussed.Comment: published version, 4 pages, revtex
Airy processes and variational problems
We review the Airy processes; their formulation and how they are conjectured
to govern the large time, large distance spatial fluctuations of one
dimensional random growth models. We also describe formulas which express the
probabilities that they lie below a given curve as Fredholm determinants of
certain boundary value operators, and the several applications of these
formulas to variational problems involving Airy processes that arise in
physical problems, as well as to their local behaviour.Comment: Minor corrections. 41 pages, 4 figures. To appear as chapter in "PASI
Proceedings: Topics in percolative and disordered systems
Strong asymptotics for Jacobi polynomials with varying nonstandard parameters
Strong asymptotics on the whole complex plane of a sequence of monic Jacobi
polynomials is studied, assuming that with and satisfying , , . The
asymptotic analysis is based on the non-Hermitian orthogonality of these
polynomials, and uses the Deift/Zhou steepest descent analysis for matrix
Riemann-Hilbert problems. As a corollary, asymptotic zero behavior is derived.
We show that in a generic case the zeros distribute on the set of critical
trajectories of a certain quadratic differential according to the
equilibrium measure on in an external field. However, when either
, or are geometrically close to ,
part of the zeros accumulate along a different trajectory of the same quadratic
differential.Comment: 31 pages, 12 figures. Some references added. To appear in Journal
D'Analyse Mathematiqu
Last passage percolation and traveling fronts
We consider a system of N particles with a stochastic dynamics introduced by
Brunet and Derrida. The particles can be interpreted as last passage times in
directed percolation on {1,...,N} of mean-field type. The particles remain
grouped and move like a traveling wave, subject to discretization and driven by
a random noise. As N increases, we obtain estimates for the speed of the front
and its profile, for different laws of the driving noise. The Gumbel
distribution plays a central role for the particle jumps, and we show that the
scaling limit is a L\'evy process in this case. The case of bounded jumps
yields a completely different behavior
Universal Distributions for Growth Processes in 1+1 Dimensions and Random Matrices
We develop a scaling theory for KPZ growth in one dimension by a detailed
study of the polynuclear growth (PNG) model. In particular, we identify three
universal distributions for shape fluctuations and their dependence on the
macroscopic shape. These distribution functions are computed using the
partition function of Gaussian random matrices in a cosine potential.Comment: 4 pages, 3 figures, 1 table, RevTeX, revised version, accepted for
publication in PR
From Vicious Walkers to TASEP
We propose a model of semi-vicious walkers, which interpolates between the
totally asymmetric simple exclusion process and the vicious walkers model,
having the two as limiting cases. For this model we calculate the asymptotics
of the survival probability for particles and obtain a scaling function,
which describes the transition from one limiting case to another. Then, we use
a fluctuation-dissipation relation allowing us to reinterpret the result as the
particle current generating function in the totally asymmetric simple exclusion
process. Thus we obtain the particle current distribution asymptotically in the
large time limit as the number of particles is fixed. The results apply to the
large deviation scale as well as to the diffusive scale. In the latter we
obtain a new universal distribution, which has a skew non-Gaussian form. For
particles its asymptotic behavior is shown to be
as and
as .Comment: 37 pages, 4 figures, Corrected reference
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