Quasi-Monte Carlo Simulation of Diffusion

A particle method adapted to the simulation of diffusion problems is presented. Time is discretized into increments of length Δt. During each time step, the particles are allowed to random walk to any point by taking steps sampled from a Gaussian distribution centered at the current particle position with variance related to the time discretization Δt. Quasi-random samples are used and the particles are relabeled according to their position at each time step. Convergence is proved for the pure initial-value problem in s space dimensions. For some simple demonstration problems, the numerical results indicate that an improvement is achieved over standard random walk simulation.     

一类带临界Sobolev指数及有拟超临界Neumann边界条件的椭圆方程正解的多重性

本文讨论了Ω上如下一类带临界增长的椭圆方程在拟超临界的Neumann边界条件下正解的存在性:-Div(| u |p-2 u) =λum up*-1,-| u |p-2 u ν=ψ(x)uq-1,x∈Ω,x∈Ω.这里Ω∈RN,(N≥3)是光滑有界区域, 1≤p < N,0< m < p-1,(N -1)pN - p= p*N-1 ≤q < p*,其中p* =NpN - p是W1,p(Ω)→Ls(Ω)的Sobolev临界指数,p*N-1 =(N -1)pN - p是W1,p(Ω)→Lt( Ω)的在(N-1)维流形上的临界指数,λ>0是一个正参数.     

Models with virtual force carriers in classical particle physics

A mathematically rigorous model of the interaction of two classical point particles without fields or forces is described. Under certain scaling, it is proved that the trajectories converge to classical ones obtained in the case of the Coulomb or gravitational interaction of two particles. The model resembles the intuitive idea of virtual particles frequently used in quantum particle physics.     

Coalescing Particles on an Interval

At time 0, we begin with a particle at each integer in [0, n]. At each positive integer time, one of the particles remaining in [1, n] is chosen at random and moved one to the left, coalescing with any particle that might already be there. How long does it take until all particles coalesce (at 0)?     

Clifford-algebraic random walks on the hypercube

The n-dimensional hypercube is a simple graph on 2ⁿ vertices labeled by binary strings, or words, of length n. Pairs of vertices are adjacent if and only if they differ in exactly one position as binary words; i.e., the Hamming distance between the words is one. A discrete-time random walk is easily defined on the hypercube by “flipping” a randomly selected digit from 0 to 1 or vice-versa at each time step. By associating the words as blades in a Clifford algebra of particular signature, combinatorial properties of the geometric product can be used to represent this random walk as a sequence within the algebra. A closed-form formula is revealed which yields probability distributions on the vertices of the hypercube at any time k ≥ 0 by a formal power series expansion of elements in the algebra. Furthermore, by inducing a walk on a larger Clifford algebra, probabilities of self-avoiding walks and expected first hitting times of specific vertices are recovered. Moreover, because the Clifford algebras used in the current work are canonically isomorphic to fermion algebras, everything appearing here can be rewritten using fermion creation/annihilation operators, making the discussion relevant to quantum mechanics and/or quantum computing.     

Bounds on the cover time

Consider a particle that moves on a connected, undirected graphG withn vertices. At each step the particle goes from the current vertex to one of its neighbors, chosen uniformly at random. Tocover time is the first time when the particle has visited all the vertices in the graph starting from a given vertex. In this paper, we present upper and lower bounds that relate the expected cover time for a graph to the eigenvalues of the Markov chain that describes the random walk above. An interesting consequence is that regular expander graphs have expected cover time (n logn).This research was done while this author was a postdoctoral fellow in the Department of Computer Science, Princeton University, and it was supported in part by DNR grant N00014-87-K-0467.     

Coalescing and annihilating random walk with ‘action at a distance’

We consider a system of particles which perform continuous time random walks onZ ^d . These random walks are independent as long as no two particles are at the same site or adjacent to each other. When a particle jumps from a site x to a sitey and there is already another particle aty or at some neighbory′ ofy, then there is an interaction. In the coalescing model, either the particle which just jumped toy is removed (or, equivalently, coalesces with a particle aty ory′) or all the particles at the sites adjacent toy (other thanx) are removed. In the annihilating random walk, the particle which just jumped toy and one particle aty ory′ annihilate each other. We prove that when the dimensiond is at least 9, then the density of this system is asymptotically equivalent toC/t for some constant C, whose value is explicitly given.     

Numerical Investigation of Particulate Flow over a Backward‐Facing Step

Flow separation and recirculation caused by a sudden expansion in the channel geometry in the form of a backwardfacing step (BFS) appear in numerous practical applications. Additionally, BFS flow has been used as a generic test case to study fundamental flow properties, such as separation or re‐attachment. In the present work, BFS flow laden with dispersed particles is investigated by numerical simulations using a spectral element method [1]. The motion of the dispersed particles is computed by Lagrangian particle tracking. In a first step, only the influence of the flow on the particles is accounted for, while possible effects of the particle motion on the flow are neglected. Spatial distribution of the particles is investigated, and effects of different wall‐particle interaction models on the computational results are examined.     

多层快速多极子方法的快速插值

多层快速多极子方法(MLFMM)可用来加速迭代求解由Maxwell方程组或Helmholtz方程导出的积分方程,其复杂度理论上是O(NlogN),N为未知量个数.MLFMM依赖于快速计算每层的转移项,以及上聚和下推过程中的层间插值.本文引入计算类似N体问题的一维快速多极子方法(FMM1D).基于FMM1D的快速Lagr...     

The Fractal Character of Localizable Measure-Valued Processes,II. Localizable Processes and Backward Trees

Regard a large population of infinitesimal particles (i.e. a measure) in the case, when the particles evolve (i.e. move, branch, die) independently of each other. Those evolutions we will call localizable. In the present part of this paper we answer at first the question about the structure of localizable evolutions, which take place in one step (independent clustering of measures). In localizable evolutions one can follow the path of any particle (and their predecessors) surviving up to some fixed time. The totality of these paths is the backward tere corresponding to this time point. In the case of continuous time localizable Markov evolutions the random backward tree measure is constructed via finite-dimensional distributions using the extension theorem from part I.     

Parallel Resampling in the Particle Filter

Modern parallel computing devices, such as the graphics processing unit (GPU), have gained significant traction in scientific and statistical computing. They are particularly well-suited to data-parallel algorithms such as the particle filter, or more generally sequential Monte Carlo (SMC), which are increasingly used in statistical inference. SMC methods carry a set of weighted particles through repeated propagation, weighting, and resampling steps. The propagation and weighting steps are straightforward to parallelize, as they require only independent operations on each particle. The resampling step is more difficult, as standard schemes require a collective operation, such as a sum, across particle weights. Focusing on this resampling step, we analyze two alternative schemes that do not involve a collective operation (Metropolis and rejection resamplers), and compare them to standard schemes (multinomial, stratified, and systematic resamplers). We find that, in certain circumstances, the alternative resamplers can perform significantly faster on a GPU, and to a lesser extent on a CPU, than the standard approaches. Moreover, in single precision, the standard approaches are numerically biased for upward of hundreds of thousands of particles, while the alternatives are not. This is particularly important given greater single- than double-precision throughput on modern devices, and the consequent temptation to use single precision with a greater number of particles. Finally, we provide auxiliary functions useful for implementation, such as for the permutation of ancestry vectors to enable in-place propagation. Supplementary materials are available online.     

Continuity for the asymptotic shape in the frog model with random initial configurations

We consider the so-called frog model with random initial configurations, which is described by the following evolution mechanism of simple random walks on the multidimensional cubic lattice: Some particles are randomly assigned to any site of the multidimensional cubic lattice. Initially, only particles at the origin are active and they independently perform simple random walks. The other particles are sleeping and do not move at first. When sleeping particles are hit by an active particle, they become active and start doing independent simple random walks. An interest of this model is how initial configurations affect the asymptotic shape of the set of all sites visited by active particles up to a certain time. Thus, in this paper, we prove continuity for the asymptotic shape in the law of the initial configuration.     

Limit Theorems for Supercritical Branching Random Fields

An infinite particle system in R^d is considered where the initial distribution is POISSON ian and each initial particle gives rise to a supercritical age-dependent branching process with the particles moving randomly in space. Our approach differs from the usual: instead of the point measures determined by the locations of the particles at each time, we take the particles at a “final time” and observe the past histories of their ancestry lines. A law of large numbers and a central limit theorem are proved under a space-time scaling representing high density of particles and small mean particle lifetime. The fluctuation limit is a generalized GAUSS -MARKOV process with continuous trajectories and satisfies a deterministic evolution equation with generalized random initial condition. A more precise form of the central limit theorem is obtained in the case of particles performing BROWN ian motion and having exponentially distributed lifetime.     

Existence of an infinite particle limit of stochastic ranking process

We study a stochastic particle system which models the time evolution of the ranking of books by online bookstores (e.g., Amazon.co.jp). In this system, particles are lined in a queue. Each particle jumps at random jump times to the top of the queue, and otherwise stays in the queue, being pushed toward the tail every time another particle jumps to the top. In an infinite particle limit, the random motion of each particle between its jumps converges to a deterministic trajectory. (This trajectory is actually observed in the ranking data on web sites.) We prove that the (random) empirical distribution of this particle system converges to a deterministic space–time-dependent distribution. A core of the proof is the law of large numbers for dependent random variables.     

Mean fixation time estimates in constant size populations

We consider a population consisting of N particles each of which some type is ascribed to. All particles die at the integer time moments and produce a random amount of particles of the same type as the parent. Moreover, the population retains its size N and the random vectors defining the number of offsprings of each particle have exchangeable distributions. We obtain several upper bounds for the expectation of the variable equal to the number of the generation when all particles in the population become single-type or almost single-type. Here we fix an arbitrary initial configuration of particles according to types.     

球面介质作用下的测度值分枝过程

我们考虑空间上一粒子系统，当其受到分布于求面上的介质作进行粒子分枝和衍生，产生新了体，而新粒子仍按原粒子的运动规则继续空间运动。通过合理的假设和极限过程，粒子在空间的散布一测度值分枝过程来刻划。     

On nested code pairs from the Hermitian curve

Nested code pairs play a crucial role in the construction of ramp secret sharing schemes [15] and in the CSS construction of quantum codes [14]. The important parameters are (1) the codimension, (2) the relative minimum distance of the codes, and (3) the relative minimum distance of the dual set of codes. Given values for two of them, one aims at finding a set of nested codes having parameters with these values and with the remaining parameter being as large as possible. In this work we study nested codes from the Hermitian curve. For not too small codimension, we present improved constructions and provide closed formula estimates on their performance. For small codimension we show how to choose pairs of one-point algebraic geometric codes in such a way that one of the relative minimum distances is larger than the corresponding non-relative minimum distance.     

Genealogy of extremal particles of branching Brownian motion

Branching Brownian motion describes a system of particles that diffuse in space and split into offspring according to a certain random mechanism. By virtue of the groundbreaking work by M. Bramson on the convergence of solutions of the Fisher‐KPP equation to traveling waves, the law of the rightmost particle in the limit of large times is rather well understood. In this work, we address the full statistics of the extremal particles (first‐, second‐, third‐largest, etc.). In particular, we prove that in the large t‐limit, such particles descend with overwhelming probability from ancestors having split either within a distance of order 1 from time 0, or within a distance of order 1 from time t. The approach relies on characterizing, up to a certain level of precision, the paths of the extremal particles. As a byproduct, a heuristic picture of branching Brownian motion “at the edge” emerges, which sheds light on the still unknown limiting extremal process. © 2011 Wiley Periodicals, Inc.     

Towards Fully Discretized Differential Inclusions

Euler schemes for the calculation of the solution set for a differential inclusion are investigated. Under Lipschitz and convexity conditions on the set-valued map the usual O(h)-approximation, h denoting the time step, is preserved, if one uses only boundary points in each step. An O( )-approximation is achieved, if one uses only extremal points. So, in case that the extremal sets are finite, a full discretization of the differential inclusion is performed.     

The survival of branching annihilating random walk

Summary Branching annihilating random walk is an interacting particle system on . As time evolves, particles execute random walks and branch, and disappear when they meet other particles. It is shown here that starting from a finite number of particles, the system will survive with positive probability if the random walk rate is low enough relative to the branching rate, but will die out with probability one if the random walk rate is high. Since the branching annihilating random walk is non-attractive, standard techniques usually employed for interacting particle systems are not applicable. Instead, a modification of a contour argument by Gray and Griffeath is used.