2,181 research outputs found
Random billiards with wall temperature and associated Markov chains
By a random billiard we mean a billiard system in which the standard specular
reflection rule is replaced with a Markov transition probabilities operator P
that, at each collision of the billiard particle with the boundary of the
billiard domain, gives the probability distribution of the post-collision
velocity for a given pre-collision velocity. A random billiard with
microstructure (RBM) is a random billiard for which P is derived from a choice
of geometric/mechanical structure on the boundary of the billiard domain. RBMs
provide simple and explicit mechanical models of particle-surface interaction
that can incorporate thermal effects and permit a detailed study of
thermostatic action from the perspective of the standard theory of Markov
chains on general state spaces.
We focus on the operator P itself and how it relates to the
mechanical/geometric features of the microstructure, such as mass ratios,
curvatures, and potentials. The main results are as follows: (1) we
characterize the stationary probabilities (equilibrium states) of P and show
how standard equilibrium distributions studied in classical statistical
mechanics, such as the Maxwell-Boltzmann distribution and the Knudsen cosine
law, arise naturally as generalized invariant billiard measures; (2) we obtain
some basic functional theoretic properties of P. Under very general conditions,
we show that P is a self-adjoint operator of norm 1 on an appropriate Hilbert
space. In a simple but illustrative example, we show that P is a compact
(Hilbert-Schmidt) operator. This leads to the issue of relating the spectrum of
eigenvalues of P to the features of the microstructure;(3) we explore the
latter issue both analytically and numerically in a few representative
examples;(4) we present a general algorithm for simulating these Markov chains
based on a geometric description of the invariant volumes of classical
statistical mechanics
Sampling constrained probability distributions using Spherical Augmentation
Statistical models with constrained probability distributions are abundant in
machine learning. Some examples include regression models with norm constraints
(e.g., Lasso), probit, many copula models, and latent Dirichlet allocation
(LDA). Bayesian inference involving probability distributions confined to
constrained domains could be quite challenging for commonly used sampling
algorithms. In this paper, we propose a novel augmentation technique that
handles a wide range of constraints by mapping the constrained domain to a
sphere in the augmented space. By moving freely on the surface of this sphere,
sampling algorithms handle constraints implicitly and generate proposals that
remain within boundaries when mapped back to the original space. Our proposed
method, called {Spherical Augmentation}, provides a mathematically natural and
computationally efficient framework for sampling from constrained probability
distributions. We show the advantages of our method over state-of-the-art
sampling algorithms, such as exact Hamiltonian Monte Carlo, using several
examples including truncated Gaussian distributions, Bayesian Lasso, Bayesian
bridge regression, reconstruction of quantized stationary Gaussian process, and
LDA for topic modeling.Comment: 41 pages, 13 figure
2D growth processes: SLE and Loewner chains
This review provides an introduction to two dimensional growth processes.
Although it covers a variety processes such as diffusion limited aggregation,
it is mostly devoted to a detailed presentation of stochastic Schramm-Loewner
evolutions (SLE) which are Markov processes describing interfaces in 2D
critical systems. It starts with an informal discussion, using numerical
simulations, of various examples of 2D growth processes and their connections
with statistical mechanics. SLE is then introduced and Schramm's argument
mapping conformally invariant interfaces to SLE is explained. A substantial
part of the review is devoted to reveal the deep connections between
statistical mechanics and processes, and more specifically to the present
context, between 2D critical systems and SLE. Some of the SLE remarkable
properties are explained, as well as the tools for computing with SLE. This
review has been written with the aim of filling the gap between the
mathematical and the physical literatures on the subject.Comment: A review on Stochastic Loewner evolutions for Physics Reports, 172
pages, low quality figures, better quality figures upon request to the
authors, comments welcom
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