Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userDependent particle deposition on a graph: concentration properties of the height profile
162
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We present classes of models in which particles are dropped on an arbitrary fixed finite connected graph, obeying adhesion rules with screening. We prove that there is an invariant distribution for the resulting height profile, and Gaussian concentration for functions depending on the paths of the profiles. As a corollary we obtain a law of large numbers for the maximum height. This describes the asymptotic speed with which the maximal height increases. The results incorporate the case of independent particle droppings but extend to droppings according to a driving Markov chain, and to droppings with possible deposition below the top layer up to a fixed finite depth, obeying a non-nullness condition for the screening rule. The proof is based on an analysis of the Markov chain on height-profiles using coupling methods. We construct a finite communicating set of configurations of profiles to which the chain keeps returning.
rate research
Read More
In this paper we study uniformly random lozenge tilings of strip domains. Under the assumption that the limiting arctic boundary has at most one cusp, we prove a nearly optimal concentration estimate for the tiling height functions and arctic boundaries on such domains: with overwhelming probability the tiling height function is within $n^delta$ of its limit shape, and the tiling arctic boundary is within $n^{1/3+delta}$ to its limit shape, for arbitrarily small $delta>0$. This concentration result will be used in [AH21] to prove that the edge statistics of simply-connected polygonal domains, subject to a technical assumption on their limit shape, converge to the Airy line ensemble.
We study the Fleming-Viot particle process formed by N interacting continuous-time asymmetric random walks on the cycle graph, with uniform killing. We show that this model has a remarkable exact solvability, despite the fact that it is non-reversible with non-explicit invariant distribution. Our main results include quantitative propagation of chaos and exponential ergodicity with explicit constants, as well as formulas for covariances at equilibrium in terms of the Chebyshev polynomials. We also obtain a bound uniform in time for the convergence of the proportion of particles in each state when the number of particles goes to infinity.
This paper is concerned with symmetric $1$-dependent colorings of the $d$-ray star graph $mathscr{S}^d$ for each $d ge 2$. We compute the critical point of the $1$-dependent hard-core processes on $mathscr{S}^d$, which gives a lower bound for the number of colors needed for a $1$-dependent coloring of $mathscr{S}^d$. We provide an explicit construction of a $1$-dependent $q$-coloring for any $q ge 5$ of the infinite subgraph $mathscr{S}^3_{(1,1,infty)}$, which is symmetric in the colors and whose restriction to any copy of $mathbb{Z}$ is some symmetric $1$-dependent $q$-coloring of $mathbb{Z}$. We also prove that there is no such coloring of $mathscr{S}^3_{(1,1,infty)}$ with $q = 4$ colors. A list of open problems are presented.
In this paper, we consider graphon particle systems with heterogeneous mean-field type interactions and the associated finite particle approximations. Under suitable growth (resp. convexity) assumptions, we obtain uniform-in-time concentration estimates, over finite (resp. infinite) time horizon, for the Wasserstein distance between the empirical measure and its limit, extending the work of Bolley--Guillin--Villani.
Mixtures are convex combinations of laws. Despite this simple definition, a mixture can be far more subtle than its mixed components. For instance, mixing Gaussian laws may produce a potential with multiple deep wells. We study in the present work fine properties of mixtures with respect to concentration of measure and Sobolev type functional inequalities. We provide sharp Laplace bounds for Lipschitz functions in the case of generic mixtures, involving a transportation cost diameter of the mixed family. Additionally, our analysis of Sobolev type inequalities for two-component mixtures reveals natural relations with some kind of band isoperimetry and support constrained interpolation via mass transportation. We show that the Poincare constant of a two-component mixture may remain bounded as the mixture proportion goes to 0 or 1 while the logarithmic Sobolev constant may surprisingly blow up. This counter-intuitive result is not reducible to support disconnections, and appears as a reminiscence of the variance-entropy comparison on the two-point space. As far as mixtures are concerned, the logarithmic Sobolev inequality is less stable than the Poincare inequality and the sub-Gaussian concentration for Lipschitz functions. We illustrate our results on a gallery of concrete two-component mixtures. This work leads to many open questions.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
