arXiv subjects

E. Ben-Naim

Publications and source records attributed to E. Ben-Naim.

At least 19 recordsLinked to original sources

arXiv2022

Statistical properties of sites visited by independent random walks

The set of visited sites and the number of visited sites are two basic properties of the random walk trajectory. We consider two independent random walks on a hyper-cubic lattice and study ordering probabilities associated with these characteristics. The first is the probability that during the time interval (0,t), the number of sites visited by a walker never exceeds that of another walker. The second is the probability that the sites visited by a walker remain a subset of the sites visited by another walker. Using numerical simulations, we investigate the leading asymptotic behaviors of the ordering probabilities in spatial dimensions d=1,2,3,4. We also study the evolution of the number of ties between the number of visited sites. We show analytically that the average number of ties increases as $a_1\ln t$ with $a_1=0.970508$ in one dimension and as $(\ln t)^2$ in two dimensions.

cond-mat.stat-mech↗

arXiv2021

Monotonicity in the averaging process

We investigate an averaging process that describes how interacting agents approach consensus through binary interactions. In each elementary step, two agents are selected at random and they reach compromise by adopting their opinion average. We show that the fraction of agents with a monotonically decreasing opinion decays as $e^{-αt}$, and that the exponent $α=\tfrac{1}{2}-\tfrac{1+\ln \ln 2}{4\ln 2}$ is selected as the extremum from a continuous spectrum of possible values. The opinion distribution of monotonic agents is asymmetric, and it becomes self-similar at large times. Furthermore, the tails of the opinion distribution are algebraic, and they are characterized by two distinct and nontrivial exponents. We also explore statistical properties of agents with an opinion strictly above average.

cond-mat.stat-mech↗

arXiv2019

Jamming and Tiling in Fragmentation of Rectangles

We investigate a stochastic process where a rectangle breaks into smaller rectangles through a series of horizontal and vertical fragmentation events. We focus on the case where both the vertical size and the horizontal size of a rectangle are discrete variables. Because of this constraint, the system reaches a jammed state where all rectangles are sticks, that is, rectangles with minimal width. Sticks are frozen as they can not break any further. The average number of sticks in the jammed state, $S$, grows as $S\simeq A/\sqrt{2π\ln A}$ with rectangle area $A$ in the large-area limit, and remarkably, this behavior is independent of the aspect ratio. The distribution of stick length has a power-law tail, and further, its moments are characterized by a nonlinear spectrum of scaling exponents. We also study an asymmetric breakage process where vertical and horizontal fragmentation events are realized with different probabilities. In this case, there is a phase transition between a weakly asymmetric phase where the length distribution is independent of system size, and a strongly asymmetric phase where this distribution depends on system size.

cond-mat.stat-mech↗

arXiv2018

Jamming and Tiling in Aggregation of Rectangles

We study a random aggregation process involving rectangular clusters. In each aggregation event, two rectangles are chosen at random and if they have a compatible side, either vertical or horizontal, they merge along that side to form a larger rectangle. Starting with $N$ identical squares, this elementary event is repeated until the system reaches a jammed state where each rectangle has two unique sides. The average number of frozen rectangles scales as $N^α$ in the large-$N$ limit. The growth exponent $α=0.229\pm 0.002$ characterizes statistical properties of the jammed state and the time-dependent evolution. We also study an aggregation process where rectangles are embedded in a plane and interact only with nearest neighbors. In the jammed state, neighboring rectangles are incompatible, and these frozen rectangles form a tiling of the two-dimensional domain. In this case, the final number of rectangles scales linearly with system size.

cond-mat.stat-mech↗

arXiv2017

Extinction and Survival in Two-Species Annihilation

We study diffusion-controlled two-species annihilation with a finite number of particles. In this stochastic process, particles move diffusively, and when two particles of opposite type come into contact, the two annihilate. We focus on the behavior in three spatial dimensions and for initial conditions where particles are confined to a compact domain. Generally, one species outnumbers the other, and we find that the difference between the number of majority and minority species, which is a conserved quantity, controls the behavior. When the number difference exceeds a critical value, the minority becomes extinct and a finite number of majority particles survive, while below this critical difference, a finite number of particles of both species survive. The critical difference $Δ_c$ grows algebraically with the total initial number of particles $N$, and when $N\gg 1$, the critical difference scales as $Δ_c\sim N^{1/3}$. Furthermore, when the initial concentrations of the two species are equal, the average number of surviving majority and minority particles, $M_+$ and $M_-$, exhibit two distinct scaling behaviors, $M_+\sim N^{1/2}$ and $M_-\sim N^{1/6}$. In contrast, when the initial populations are equal, these two quantities are comparable $M_+\sim M_-\sim N^{1/3}$.

cond-mat.stat-mech↗

arXiv2016

Kinetics of Aggregation with Choice

We generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected, and the target cluster merges with the larger of the two candidate clusters. We study the long-time asymptotic behavior, and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of novel features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tails of the density are overpopulated, at the expense of the density moderate-size clusters. We also study the complementary case where the smaller candidate clusters participates in the aggregation process, and find abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters, and a symmetric implementation where the choice is between two pairs of clusters.

cond-mat.stat-mech↗

arXiv2016

Kinetics of Diffusion-Controlled Annihilation with Sparse Initial Conditions

We study diffusion-controlled single-species annihilation with sparse initial conditions. In this random process, particles undergo Brownian motion, and when two particles meet, both disappear. We focus on sparse initial conditions where particles occupy a subspace of dimension $δ$ that is embedded in a larger space of dimension $d$. We find that the co-dimension $Δ=d-δ$ governs the behavior. All particles disappear when the co-dimension is sufficiently small, $Δ\leq 2$; otherwise, a finite fraction of particles indefinitely survive. We establish the asymptotic behavior of the probability $S(t)$ that a test particle survives until time $t$. When the subspace is a line, $δ=1$, we find inverse logarithmic decay, $S\sim (\ln t)^{-1}$, in three dimensions, and a modified power-law decay, $S\sim (\ln t)\,t^{-1/2}$, in two dimensions. In general, the survival probability decays algebraically when $Δ<2$, and there is an inverse logarithmic decay at the critical co-dimension $Δ=2$.

cond-mat.stat-mech↗

arXiv2016

Escape and Finite-Size Scaling in Diffusion-Controlled Annihilation

We study diffusion-controlled single-species annihilation with a finite number of particles. In this reaction-diffusion process, each particle undergoes ordinary diffusion, and when two particles meet, they annihilate. We focus on spatial dimensions $d>2$ where a finite number of particles typically survive the annihilation process. Using the rate equation approach and scaling techniques we investigate the average number of surviving particles, $M$, as a function of the initial number of particles, $N$. In three dimensions, for instance, we find the scaling law $M\sim N^{1/3}$ in the asymptotic regime $N\gg 1$. We show that two time scales govern the reaction kinetics: the diffusion time scale, $T\sim N^{2/3}$, and the escape time scale, $τ\sim N^{4/3}$. The vast majority of annihilation events occur on the diffusion time scale, while no annihilation events occur beyond the escape time scale.

cond-mat.stat-mech↗

arXiv2016

Maxima of Two Random Walks: Universal Statistics of Lead Changes

We investigate statistics of lead changes of the maxima of two discrete-time random walks in one dimension. We show that the average number of lead changes grows as $π^{-1}\ln(t)$ in the long-time limit. We present theoretical and numerical evidence that this asymptotic behavior is universal. Specifically, this behavior is independent of the jump distribution: the same asymptotic underlies standard Brownian motion and symmetric Levy flights. We also show that the probability to have at most n lead changes behaves as $t^{-1/4}[\ln t]^n$ for Brownian motion and as $t^{-β(μ)}[\ln t]^n$ for symmetric Levy flights with index $μ$. The decay exponent $β(μ)$ varies continuously with the Levy index when $0<μ<2$, while $β=1/4$ for $μ>2$.

cond-mat.stat-mech↗

arXiv2015

Scaling Exponents for Ordered Maxima

We study extreme value statistics of multiple sequences of random variables. For each sequence with N variables, independently drawn from the same distribution, the running maximum is defined as the largest variable to date. We compare the running maxima of m independent sequences, and investigate the probability S_N that the maxima are perfectly ordered, that is, the running maximum of the first sequence is always larger than that of the second sequence, which is always larger than the running maximum of the third sequence, and so on. The probability S_N is universal: it does not depend on the distribution from which the random variables are drawn. For two sequences, S_N ~ N^(-1/2), and in general, the decay is algebraic, S_N ~ N^(-σ_m), for large N. We analytically obtain the exponent sigma_3= 1.302931 as root of a transcendental equation. Furthermore, the exponents sigma_m grow with m, and we show that sigma_m ~ m for large m.

cond-mat.stat-mech↗

arXiv2015

Pattern Selection and Super-patterns in the Bounded Confidence Model

We study pattern formation in the bounded confidence model of opinion dynamics. In this random process, opinion is quantified by a single variable. Two agents may interact and reach a fair compromise, but only if their difference of opinion falls below a fixed threshold. Starting from a uniform distribution of opinions with compact support, a traveling wave forms and it propagates from the domain boundary into the unstable uniform state. Consequently, the system reaches a steady state with isolated clusters that are separated by distance larger than the interaction range. These clusters form a quasi-periodic pattern where the sizes of the clusters and the separations between them are nearly constant. We obtain analytically the average separation between clusters L. Interestingly, there are also very small quasi-periodic modulations in the size of the clusters. The spatial periods of these modulations are a series of integers that follow from the continued fraction representation of the irrational average separation L.

nlin.PS↗

arXiv2015

Irreversible Reactions and Diffusive Escape: Stationary Properties

We study three basic diffusion-controlled reaction processes -- annihilation, coalescence, and aggregation. We examine the evolution starting with the most natural inhomogeneous initial configuration where a half-line is uniformly filled by particles, while the complementary half-line is empty. We show that the total number of particles that infiltrate the initially empty half-line is finite and has a stationary distribution. We determine the evolution of the average density from which we derive the average total number N of particles in the initially empty half-line; e.g., for annihilation \langle N\rangle = 3/16+1/(4π). For the coalescence process, we devise a procedure that in principle allows one to compute P(N), the probability to find exactly N particles in the initially empty half-line; we complete the calculations in the first non-trivial case (N=1). As a by-product we derive the distance distribution between the two leading particles.

cond-mat.stat-mech↗

arXiv2014

Fragmentation of Random Trees

We study fragmentation of a random recursive tree into a forest by repeated removal of nodes. The initial tree consists of N nodes and it is generated by sequential addition of nodes with each new node attaching to a randomly-selected existing node. As nodes are removed from the tree, one at a time, the tree dissolves into an ensemble of separate trees, namely, a forest. We study statistical properties of trees and nodes in this heterogeneous forest, and find that the fraction of remaining nodes m characterizes the system in the limit N --> infty. We obtain analytically the size density phi_s of trees of size s. The size density has power-law tail phi_s ~ s^(-alpha) with exponent alpha=1+1/m. Therefore, the tail becomes steeper as further nodes are removed, and the fragmentation process is unusual in that exponent alpha increases continuously with time. We also extend our analysis to the case where nodes are added as well as removed, and obtain the asymptotic size density for growing trees.

cond-mat.stat-mech↗

arXiv2014

Slow Kinetics of Brownian Maxima

We study extreme-value statistics of Brownian trajectories in one dimension. We define the maximum as the largest position to date and compare maxima of two particles undergoing independent Brownian motion. We focus on the probability P(t) that the two maxima remain ordered up to time t, and find the algebraic decay P ~ t^(-beta) with exponent beta=1/4. When the two particles have diffusion constants D1 and D2, the exponent depends on the mobilities, beta=(1/pi)arctan[sqrt(D2/D1)]. We also use numerical simulations to investigate maxima of multiple particles in one dimension and the largest extension of particles in higher dimensions.

cond-mat.stat-mech↗

arXiv2014

Persistence of Random Walk Records

We study records generated by Brownian particles in one dimension. Specifically, we investigate an ordinary random walk and define the record as the maximal position of the walk. We compare the record of an individual random walk with the mean record, obtained as an average over infinitely many realizations. We term the walk "superior" if the record is always above average, and conversely, the walk is said to be "inferior" if the record is always below average. We find that the fraction of superior walks, S, decays algebraically with time, S ~ t^(-beta), in the limit t --> infty, and that the persistence exponent is nontrivial, beta=0.382258.... The fraction of inferior walks, I, also decays as a power law, I ~ t^(-alpha), but the persistence exponent is smaller, alpha=0.241608.... Both exponents are roots of transcendental equations involving the parabolic cylinder function. To obtain these theoretical results, we analyze the joint density of superior walks with given record and position, while for inferior walks it suffices to study the density as function of position.

cond-mat.stat-mech↗

arXiv2013

Scaling Exponent for Incremental Records

We investigate records in a growing sequence of identical and independently distributed random variables. The record equals the largest value in the sequence, and our focus is on the increment, defined as the difference between two successive records. We investigate sequences in which all increments decrease monotonically, and find that the fraction I_N of sequences that exhibit this property decays algebraically with sequence length N, namely I_N ~ N^{-nu} as N --> infinity. We analyze the case where the random variables are drawn from a uniform distribution with compact support, and obtain the exponent nu = 0.317621... using analytic methods. We also study the record distribution and the increment distribution. Whereas the former is a narrow distribution with an exponential tail, the latter is broad and has a power-law tail characterized by the exponent nu. Empirical analysis of records in the sequence of waiting times between successive earthquakes is consistent with the theoretical results.

cond-mat.stat-mech↗

arXiv2013

Statistics of Superior Records

We study statistics of records in a sequence of random variables. These identical and independently distributed variables are drawn from the parent distribution rho. The running record equals the maximum of all elements in the sequence up to a given point. We define a superior sequence as one where all running records are above the average record, expected for the parent distribution rho. We find that the fraction of superior sequences S_N decays algebraically with sequence length N, S_N ~ N^{-beta} in the limit N-->infty. Interestingly, the decay exponent beta is nontrivial, being the root of an integral equation. For example, when rho is a uniform distribution with compact support, we find beta=0.450265. In general, the tail of the parent distribution governs the exponent beta. We also consider the dual problem of inferior sequences, where all records are below average, and find that the fraction of inferior sequences I_N decays algebraically, albeit with a different decay exponent, I_N ~ N^{-alpha}. We use the above statistical measures to analyze earthquake data.

cond-mat.stat-mech↗

arXiv2013

First Passage in Conical Geometry and Ordering of Brownian Particles

We survey recent results on first-passage processes in unbounded cones and their applications to ordering of particles undergoing Brownian motion in one dimension. We first discuss the survival probability S(t) that a diffusing particle, in arbitrary spatial dimension, remains inside a conical domain up to time t. In general, this quantity decays algebraically S ~ t^{-beta} in the long-time limit. The exponent beta depends on the opening angle of the cone and the spatial dimension, and it is root of a transcendental equation involving the associated Legendre functions. The exponent becomes a function of a single scaling variable in the limit of large spatial dimension. We then describe two first-passage problems involving the order of N independent Brownian particles in one dimension where survival probabilities decay algebraically as well. To analyze these problems, we identify the trajectories of the N particles with the trajectory of one particle in N dimensions, confined to within a certain boundary, and we use a circular cone with matching solid angle as a replacement for the confining boundary. For N=3, the confining boundary is a wedge and the approach is exact. In general, this "cone approximation" gives strict lower bounds as well as useful estimates or the first-passage exponents. Interestingly, the cone approximation becomes asymptotically exact when N-->infinity as it predicts the exact scaling function that governs the spectrum of first-passage exponents.

cond-mat.stat-mech↗