Probabilities of Sentences about Very Sparse Random Graphs

We consider random graphs with edge probability βn^?α, where n is the number of vertices of the graph, β > 0 is fixed, and α = 1 or α = (l + 1) /l for some fixed positive integer l. We prove that for every first-order sentence, the probability that the sentence is true for the random graph has an asymptotic limit.     

Rapid mixing of Gibbs sampling on graphs that are sparse on average

Gibbs sampling also known as Glauber dynamics is a popular technique for sampling high dimensional distributions defined on graphs. Of special interest is the behavior of Gibbs sampling on the Erd?s‐Rényi random graph G(n,d/n), where each edge is chosen independently with probability d/n and d is fixed. While the average degree in G(n,d/n) is d(1 ‐ o(1)), it contains many nodes of degree of order log n/log log n. The existence of nodes of almost logarithmic degrees implies that for many natural distributions defined on G(n,p) such as uniform coloring (with a constant number of colors) or the Ising model at any fixed inverse temperature β, the mixing time of Gibbs sampling is at least n^{1+Ω(1/log log n)}. Recall that the Ising model with inverse temperature β defined on a graph G = (V,E) is the distribution over {±}^Vgiven by . High degree nodes pose a technical challenge in proving polynomial time mixing of the dynamics for many models including the Ising model and coloring. Almost all known sufficient conditions in terms of β or number of colors needed for rapid mixing of Gibbs samplers are stated in terms of the maximum degree of the underlying graph. In this work, we show that for every d < ∞ and the Ising model defined on G (n, d/n), there exists a β_d > 0, such that for all β < β_d with probability going to 1 as n →∞, the mixing time of the dynamics on G (n, d/n) is polynomial in n. Our results are the first polynomial time mixing results proven for a natural model on G (n, d/n) for d > 1 where the parameters of the model do not depend on n. They also provide a rare example where one can prove a polynomial time mixing of Gibbs sampler in a situation where the actual mixing time is slower than npolylog(n). Our proof exploits in novel ways the local tree like structure of Erd?s‐Rényi random graphs, comparison and block dynamics arguments and a recent result of Weitz. Our results extend to much more general families of graphs which are sparse in some average sense and to much more general interactions. In particular, they apply to any graph for which every vertex v of the graph has a neighborhood N(v) of radius O(log n) in which the induced sub‐graph is a tree union at most O(log n) edges and where for each simple path in N(v) the sum of the vertex degrees along the path is O(log n). Moreover, our result apply also in the case of arbitrary external fields and provide the first FPRAS for sampling the Ising distribution in this case. We finally present a non Markov Chain algorithm for sampling the distribution which is effective for a wider range of parameters. In particular, for G(n, d/n) it applies for all external fields and β < β_d, where d tanh(β_d) = 1 is the critical point for decay of correlation for the Ising model on G(n, d/n). © 2009 Wiley Periodicals, Inc. Random Struct. Alg., 2009     

On the girth of random Cayley graphs

We prove that random d‐regular Cayley graphs of the symmetric group asymptotically almost surely have girth at least (log_d‐1|G|)^1/2/2 and that random d‐regular Cayley graphs of simple algebraic groups over ??_q asymptotically almost surely have girth at least log _d‐1|G|/dim(G). For the symmetric p‐groups the girth is between loglog |G| and (log |G|)^α with α < 1. Several conjectures and open questions are presented. © 2009 Wiley Periodicals, Inc. Random Struct. Alg., 2009     

Three‐query PCPs with perfect completeness over non‐Boolean domains

We study non‐Boolean PCPs that have perfect completeness and query three positions in the proof. For the case when the proof consists of values from a domain of size d for some integer constant d ≥ 2, we construct a nonadaptive PCP with perfect completeness and soundness d^?1 + d^?2 + ?, for any constant ? > 0, and an adaptive PCP with perfect completeness and soundness d^?1 + ?, for any constant ? > 0. The latter PCP can be converted into a nonadaptive PCP with perfect completeness and soundness d^?1 + ?, for any constant ? > 0, where four positions are read from the proof. These results match the best known constructions for the case d = 2 and our proofs also show that the particular predicates we use in our PCPs are nonapproximable beyond the random assignment threshold. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2005     

Efficient algorithms for three‐dimensional axial and planar random assignment problems

Beautiful formulas are known for the expected cost of random two‐dimensional assignment problems, but in higher dimensions even the scaling is not known. In three dimensions and above, the problem has natural “Axial” and “Planar” versions, both of which are NP‐hard. For 3‐dimensional Axial random assignment instances of size n, the cost scales as Ω(1/ n), and a main result of the present paper is a linear‐time algorithm that, with high probability, finds a solution of cost O(n^–1+o(1)). For 3‐dimensional Planar assignment, the lower bound is Ω(n), and we give a new efficient matching‐based algorithm that with high probability returns a solution with cost O(n log n). © 2013 Wiley Periodicals, Inc. Random Struct. Alg., 46, 160–196, 2015     

On the complexity of branch‐and‐bound search for random trees

Let T_n be a b‐ary tree of height n, which has independent, non‐negative, identically distributed random variables associated with each of its edges, a model previously considered by Karp, Pearl, McDiarmid, and Provan. The value of a node is the sum of all the edge values on its path to the root. Consider the problem of finding the minimum leaf value of T_n. Assume that the edge random variable X is nondegenerate, has E {X^θ}<∞ for some θ>2, and satisfies bP{X=c}<1 where c is the leftmost point of the support of X. We analyze the performance of the standard branch‐and‐bound algorithm for this problem and prove that the number of nodes visited is in probability (β+o(1))ⁿ, where β∈(1, b) is a constant depending only on the distribution of the edge random variables. Explicit expressions for β are derived. We also show that any search algorithm must visit (β+o(1))ⁿ nodes with probability tending to 1, so branch‐and‐bound is asymptotically optimal where first‐order asymptotics are concerned. ©1999 John Wiley & Sons, Inc. Random Struct. Alg., 14: 309–327, 1999     

A Random Walk with Collapsing Bonds and Its Scaling Limit

Abstract

We introduce a new self-interacting random walk on the integers in a dynamic random environment and show that it converges to a pure diffusion in the scaling limit. We also find a lower bound on the diffusion coefficient in some special cases. With minor changes the same argument can be used to prove the scaling limit of the corresponding walk in ? ^d .     

Multi-scale Clustering for a Non-Markovian Spatial Branching Process

Consider a system of particles which move in R^d according to a symmetric α-stable motion, have a lifetime distribution of finite mean, and branch with an offspring law of index 1+β. In case of the critical dimension d=α/β the phenomenon of multi-scale clustering occurs. This is expressed in an fdd scaling limit theorem, where initially we start with an increasing localized population or with an increasing homogeneous Poissonian population. The limit state is uniform, but its intensity varies in line with the scaling index according to a continuous-state branching process of index 1+β. Our result generalizes the case α=2 of Brownian particles of Klenke (1998), where p.d.e. methods had been used which are not available in the present setting. Supported in part by the DFG. Supported in part by the grants RFBR 02-01-00266 and Russian Scientific School 1758.2003.1.     

Asymptotics of Damped Periodic Motions with Random Initial Speed

We consider motion on the circle, possibly with friction and external forces, the initial velocity being a large random variable. We prove that under various assumptions the probability law of the stopping position of the motion converges to a distribution depending only on the motion equation. Here the time of stopping is either a constant or the first time instant at which the velocity vanishes, and the initial velocity is of the form αU + β, where U is a fixed random variable and α and/or β tend to infinity.     

Anomalous scaling for three‐dimensional Cahn‐Hilliard fronts

We prove the stability of the one‐dimensional kink solution of the Cahn‐Hilliard equation under d‐dimensional perturbations for d ≥ 3. We also establish a novel scaling behavior of the large‐time asymptotics of the solution. The leading asymptotics of the solution is characterized by a length scale proportional to t^1/3 instead of the usual t^1/2 scaling typical to parabolic problems. © 2004 Wiley Periodicals, Inc.     

Diffusive limit of a tagged particle in asymmetric simple exclusion processes

Invariance principles are proved under diffusive scaling for the centered position of a tagged particle in the simple exclusion process with asymmetric nonzero drift jump probabilities in dimensions d ≥ 3. The method of proof is by martin‐gale techniques which rely on the fact that symmetric random walks are transient in high dimensions. © 2000 John Wiley & Sons, Inc.     

Limit theory for the random on‐line nearest‐neighbor graph

In the on‐line nearest‐neighbor graph (ONG), each point after the first in a sequence of points in ?^d is joined by an edge to its nearest neighbor amongst those points that precede it in the sequence. We study the large‐sample asymptotic behavior of the total power‐weighted length of the ONG on uniform random points in (0,1)^d. In particular, for d = 1 and weight exponent α > 1/2, the limiting distribution of the centered total weight is characterized by a distributional fixed‐point equation. As an ancillary result, we give exact expressions for the expectation and variance of the standard nearest‐neighbor (directed) graph on uniform random points in the unit interval. © 2007 Wiley Periodicals, Inc. Random Struct. Alg., 2008     

Spin depolarization decay rates in α-symmetric stable fields on cubic lattices

We study the asymptotic, long-time behavior of the energy function where {X_s : 0 ≤ s < ∞} is the standard random walk on the d-dimensional lattice Z^d, 1 < α ≤ 2, and f:R⁺ → R⁺ is any nondecreasing concave function. In the special case f(x) = x, our setting represents a lattice model for the study of transverse magnetization of spins diffusing in a homogeneous, α-stable, i.i.d., random, longitudinal field {λV(x) : x ∈ Z^d} with common marginal distribution, the standard α-symmetric stable distribution; the parameter λ describes the intensity of the field. Using large-deviation techniques, we show that S_c(λ α f) = lim_t→∞ E(t; λ f) exists. Moreover, we obtain a variational formula for this decay rate S_c. Finally, we analyze the behavior S_c(λ α f) as λ → 0 when f(x) = x^β for all 1 ≥ β > 0. Consequently, several physical conjectures with respect to lattice models of transverse magnetization are resolved by setting β = 1 in our results. We show that S_c(λ, α, 1) ≈ λ^α for d ≥ 3, λ^agr;(ln 1/λ)^α−1 in d = 2, and in d = 1. © 1996 John Wiley & Sons, Inc.     

A Jacobi spectral Galerkin method for the integrated forms of fourth‐order elliptic differential equations

This article analyzes the solution of the integrated forms of fourth‐order elliptic differential equations on a rectilinear domain using a spectral Galerkin method. The spatial approximation is based on Jacobi polynomials P (x), with α, β ∈ (?1, ∞) and n the polynomial degree. For α = β, one recovers the ultraspherical polynomials (symmetric Jacobi polynomials) and for α = β = ?½, α = β = 0, the Chebyshev of the first and second kinds and Legendre polynomials respectively; and for the nonsymmetric Jacobi polynomials, the two important special cases α = ?β = ±½ (Chebyshev polynomials of the third and fourth kinds) are also recovered. The two‐dimensional version of the approximations is obtained by tensor products of the one‐dimensional bases. The various matrix systems resulting from these discretizations are carefully investigated, especially their condition number. An algebraic preconditioning yields a condition number of O(N), N being the polynomial degree of approximation, which is an improvement with respect to the well‐known condition number O(N⁸) of spectral methods for biharmonic elliptic operators. The numerical complexity of the solver is proportional to N^d+1 for a d‐dimensional problem. This operational count is the best one can achieve with a spectral method. The numerical results illustrate the theory and constitute a convincing argument for the feasibility of the method. © 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2009     

Restricted Percolation Critical Exponents in High Dimensions

Despite great progress in the study of critical percolation on ℤ^d for d large, properties of critical clusters in high-dimensional fractional spaces and boxes remain poorly understood, unlike the situation in two dimensions. Closely related models such as critical branching random walk give natural conjectures for the value of the relevant high-dimensional critical exponents; see in particular the conjecture by Kozma-Nachmias that the probability that 0 and (n, n, n, …) are connected within [−n, n]^d scales as n^{−2 − 2d} . In this paper, we study the properties of critical clusters in high-dimensional half-spaces and boxes. In half-spaces, we show that the probability of an open connection (“arm”) from 0 to the boundary of a sidelength n box scales as n⁻³ . We also find the scaling of the half-space two-point function (the probability of an open connection between two vertices) and the tail of the cluster size distribution. In boxes, we obtain the scaling of the two-point function between vertices which are any macroscopic distance away from the boundary. Our argument involves a new application of the “mass transport" principle which we expect will be useful to obtain quantitative estimates for a range of other problems. © 2020 Wiley Periodicals LLC     

Multiple Phase Transitions in Long‐Range First‐Passage Percolation on Square Lattices

We consider a model of long‐range first‐passage percolation on the d‐dimensional square lattice ?d in which any two distinct vertices x,y ? ?^d are connected by an edge having exponentially distributed passage time with mean ‖ x – y ‖^α+o(1), where α > 0 is a fixed parameter and ‖·‖ is the l¹–norm on ?^d. We analyze the asymptotic growth rate of the set ß_t, which consists of all x ? ?^d such that the first‐passage time between the origin 0 and x is at most t as t → ∞. We show that depending on the values of α there are four growth regimes: (i) instantaneous growth for α < ^d, (ii) stretched exponential growth for α ? d,2d), (iii) superlinear growth for α ? (2d,2d + 1), and finally (iv) linear growth for α > 2d + 1 like the nearest‐neighbor first‐passage percolation model corresponding to α=∞. © 2015 Wiley Periodicals, Inc.     

The scaling window of the 2‐SAT transition

We consider the random 2‐satisfiability (2‐SAT) problem, in which each instance is a formula that is the conjunction of m clauses of the form x∨y, chosen uniformly at random from among all 2‐clauses on n Boolean variables and their negations. As m and n tend to infinity in the ratio m/n→α, the problem is known to have a phase transition at α_c=1, below which the probability that the formula is satisfiable tends to one and above which it tends to zero. We determine the finite‐size scaling about this transition, namely the scaling of the maximal window W(n, δ)=(α_?(n,δ), α₊(n,δ)) such that the probability of satisfiability is greater than 1?δ for α<α_? and is less than δ for α>α₊. We show that W(n,δ)=(1?Θ(n^?1/3), 1+Θ(n^?1/3)), where the constants implicit in Θ depend on δ. We also determine the rates at which the probability of satisfiability approaches one and zero at the boundaries of the window. Namely, for m=(1+ε)n, where ε may depend on n as long as |ε| is sufficiently small and |ε|n^1/3 is sufficiently large, we show that the probability of satisfiability decays like exp(?Θ(nε³)) above the window, and goes to one like 1?Θ(n^?1|ε|^?3 below the window. We prove these results by defining an order parameter for the transition and establishing its scaling behavior in n both inside and outside the window. Using this order parameter, we prove that the 2‐SAT phase transition is continuous with an order parameter critical exponent of 1. We also determine the values of two other critical exponents, showing that the exponents of 2‐SAT are identical to those of the random graph. © 2001 John Wiley & Sons, Inc. Random Struct. Alg., 18: 201–256 2001     

Voronoi Diagrams and Convex Hulls of Random Moving Points

This report considers the expected combinatorial complexity of the Euclidean Voronoi diagram and the convex hull of sets of n independent random points moving in unit time between two positions drawn independently from the same distribution in R ^d for fixed d\ge 2 as n→∈fty . It is proved that, when the source and destination distributions are the uniform distribution on the unit d -ball, these complexities are Θ(n ^(d+1)/d ) for the Voronoi diagram and O(n ^(d-1)/(d+1) log n) for the convex hull. Additional results for the convex hull are O( log ^d n) for the uniform distribution in the unit d -cube and O( log ^(d+1)/2 n) for the d -dimensional normal distribution. Received November 23, 1998, and in revised form July 8, 1999.     

On Sequential Fixed-Size Confidence Regions for the Mean Vector

In order to construct a fixed-size confidence region for the mean vector of an unknown distribution functionF, a new purely sequential sampling strategy is proposed first. For this new procedure, under some regularity conditions onF, the coverage probability is shown (Theorem 2.1) to be at least (1−α)−Bα²d²+o(d²) asd→0, where (1−α) is the preassigned level of confidence,Bis an appropriate functional ofF, and 2dis the preassigned diameter of the proposed spherical confidence region for the mean vector ofF. An accelerated version of the stopping rule is also provided with the analogous second-order characteristics (Theorem 3.1). In the special case of ap-dimensional normal random variable, analogous purely sequential and accelerated sequential procedures as well as a three-stage procedure are briefly introduced together with their asymptotic second-order characteristics.     

Enumeration and randomized constructions of hypertrees

Over 30 years ago, Kalai proved a beautiful d‐dimensional analog of Cayley's formula for the number of n‐vertex trees. He enumerated d‐dimensional hypertrees weighted by the squared size of their (d ? 1)‐dimensional homology group. This, however, does not answer the more basic problem of unweighted enumeration of d‐hypertrees, which is our concern here. Our main result, Theorem 1.4, significantly improves the lower bound for the number of d‐hypertrees. In addition, we study a random 1‐out model of d‐complexes where every (d ? 1)‐dimensional face selects a random d‐face containing it, and show that it has a negligible d‐dimensional homology.