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This paper studies higher index theory for a random sequence of bounded degree, finite graphs with diameter tending to infinity. We show that in a natural model for such random sequences the following hold almost surely: the coarse…

K-Theory and Homology · Mathematics 2014-04-28 Rufus Willett

Quantum random walks are constructed on operator spaces with the aid of matrix-space lifting, a type of ampliation intermediate between those provided by spatial and ultraweak tensor products. Using a form of Wiener-Ito decomposition, a…

Operator Algebras · Mathematics 2010-03-16 Alexander C. R. Belton

We propose a family of lagged random walk sampling methods in simple undirected graphs, where transition to the next state (i.e. node) depends on both the current and previous states -- hence, lagged. The existing random walk sampling…

Statistics Theory · Mathematics 2022-05-16 Li-Chun Zhang

We use Stein's method to establish the rates of normal approximation in terms of the total variation distance for a large class of sums of score functions of marked Poisson point processes on $\mathbb{R}^d$. As in the study under the weaker…

Probability · Mathematics 2020-11-17 Tianshu Cong , Aihua Xia

The term "strong approximation" is used to describe phenomena where an arithmetic group as well as all of its Zariski dense subgroups have a large image in the congruence quotients. We exhibit analogues of such phenomena in a probabilistic,…

Combinatorics · Mathematics 2009-05-05 Yair Glasner

We describe a very general abstract form of sieve based on a large sieve inequality which generalizes both the classical sieve inequality of Montgomery (and its higher-dimensional variants), and our recent sieve for Frobenius over function…

Number Theory · Mathematics 2007-05-23 Emmanuel Kowalski

This paper introduces a new Importance Sampling scheme, called Adaptive Twisted Importance Sampling, which is adequate for the improved estimation of rare event probabilities in he range of moderate deviations pertaining to the empirical…

Computation · Statistics 2009-10-13 Michel Broniatowski , Ya'Acov Ritov

We consider convex hulls of random walks whose steps belong to the domain of attraction of a stable law in $\mathbb{R}^d$. We prove convergence of the convex hull in the space of all convex and compact subsets of $\mathbb{R}^d$, equipped…

Probability · Mathematics 2022-02-28 Wojciech Cygan , Nikola Sandrić , Stjepan Šebek

We study the behavior of the random walk in a continuum independent long-range percolation model, in which two given vertices $x$ and $y$ are connected with probability that asymptotically behaves like $|x-y|^{-\alpha}$ with $\alpha>d$,…

Probability · Mathematics 2022-09-30 Ercan Sönmez , Arnaud Rousselle

We consider a real random walk S_n = X_1 + ... + X_n attracted (without centering) to the normal law: this means that for a suitable norming sequence a_n we have the weak convergence S_n / a_n --> f(x) dx, where f(x) is the standard normal…

Probability · Mathematics 2007-05-23 Francesco Caravenna

In this paper, we develop a way to extract information about a random walk associated with a typical Thurston's construction. We first observe that a typical Thurston's construction entails a free group of rank 2. We also present a proof of…

Geometric Topology · Mathematics 2021-02-18 Hyungryul Baik , Inhyeok Choi , Dongryul M. Kim

This note presents a proof of P\'olya's random walk theorem using classical methods from special function theory and asymptotic analysis.

Probability · Mathematics 2013-04-19 Jonathan Novak

In this article, we develop a theory for understanding the traces left by a random walk in the vicinity of a randomly chosen reference vertex. The analysis is related to interlacements but goes beyond previous research by showing weak limit…

Probability · Mathematics 2024-03-25 Steffen Dereich

Over the last two decades, network theory has shown to be a fruitful paradigm in understanding the organization and functioning of real-world complex systems. One technique helpful to this endeavor is identifying functionally influential…

Physics and Society · Physics 2022-01-24 Francesco Picciolo , Franco Ruzzenenti , Petter Holme , Rossana Mastrandrea

We demonstrate a novel strong law of large numbers for branching processes, with a simple proof via measure-theoretic manipulations and spine theory. Roughly speaking, any sequence of events that eventually occurs almost surely for the…

Probability · Mathematics 2013-03-01 Simon C. Harris , Matthew I. Roberts

We formulate and prove a general weak limit theorem for quantum random walks in one and more dimensions. With $X_n$ denoting position at time $n$, we show that $X_n/n$ converges weakly as $n \to \infty$ to a certain distribution which is…

Quantum Physics · Physics 2009-11-10 Geoffrey Grimmett , Svante Janson , Petra Scudo

The flow of ideas has been extensively studied by physicists, psychologists, and machine learning engineers. This paper adopts specific tools from microrheology to investigate the similarity-based flow of ideas. We introduce a random walker…

Computation and Language · Computer Science 2023-08-01 Debayan Dasgupta

Given a random walk $(S_n)$ with typical step distributed according to some fixed law and a fixed parameter $p \in (0,1)$, the associated positively step-reinforced random walk is a discrete-time process which performs at each step, with…

Probability · Mathematics 2022-10-19 Marco Bertenghi , Alejandro Rosales-Ortiz

Conditions are provided under which an endomorphism on quasisymmetric functions gives rise to a left random walk on the descent algebra which is also a lumping of a left random walk on permutations. Spectral results are also obtained.…

Combinatorics · Mathematics 2007-09-12 Patricia Hersh , Samuel K. Hsiao

We present a novel quasi-Monte Carlo mechanism to improve graph-based sampling, coined repelling random walks. By inducing correlations between the trajectories of an interacting ensemble such that their marginal transition probabilities…

Machine Learning · Statistics 2024-05-27 Isaac Reid , Eli Berger , Krzysztof Choromanski , Adrian Weller
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