The fundamental matrix for a certain random walk

1999 ◽  
Vol 36 (2) ◽  
pp. 320-333 ◽  
Author(s):  
Howard M. Taylor

Consider the random walk {Sn} whose summands have the distribution P(X=0) = 1-(2/π), and P(X = ± n) = 2/[π(4n2−1)], for n ≥ 1. This random walk arises when a simple random walk in the integer plane is observed only at those instants at which the two coordinates are equal. We derive the fundamental matrix, or Green function, for the process on the integral [0,N] = {0,1,…,N}, and from this, an explicit formula for the mean time xk for the random walk starting from S0 = k to exit the interval. The explicit formula yields the limiting behavior of xk as N → ∞ with k fixed. For the random walk starting from zero, the probability of exiting the interval on the right is obtained. By letting N → ∞ in the fundamental matrix, the Green function on the interval [0,∞) is found, and a simple and explicit formula for the probability distribution of the point of entry into the interval (−∞,0) for the random walk starting from k = 0 results. The distributions for some related random variables are also discovered.Applications to stress concentration calculations in discrete lattices are briefly reviewed.

1999 ◽  
Vol 36 (02) ◽  
pp. 320-333
Author(s):  
Howard M. Taylor

Consider the random walk {Sn} whose summands have the distributionP(X=0) = 1-(2/π), andP(X= ±n) = 2/[π(4n2−1)], forn≥ 1. This random walk arises when a simple random walk in the integer plane is observed only at those instants at which the two coordinates are equal. We derive the fundamental matrix, or Green function, for the process on the integral [0,N] = {0,1,…,N}, and from this, an explicit formula for the mean timexkfor the random walk starting fromS0=kto exit the interval. The explicit formula yields the limiting behavior ofxkasN→ ∞ withkfixed. For the random walk starting from zero, the probability of exiting the interval on the right is obtained. By lettingN→ ∞ in the fundamental matrix, the Green function on the interval [0,∞) is found, and a simple and explicit formula for the probability distribution of the point of entry into the interval (−∞,0) for the random walk starting fromk= 0 results. The distributions for some related random variables are also discovered.Applications to stress concentration calculations in discrete lattices are briefly reviewed.


2005 ◽  
Vol 42 (1) ◽  
pp. 295-301 ◽  
Author(s):  
Nadine Guillotin-Plantard

We consider a random walker on a d-regular graph. Starting from a fixed vertex, the first step is a unit step in any one of the d directions, with common probability 1/d for each one. At any later step, the random walker moves in any one of the directions, with probability q for a reversal of direction and probability p for any other direction. This model was introduced and first studied by Gillis (1955), in the case when the graph is a d-dimensional square lattice. We prove that the Gillis random walk on a d-regular graph is recurrent if and only if the simple random walk on the graph is recurrent. The Green function of the Gillis random walk will be also given, in terms of that of the simple random walk.


2005 ◽  
Vol 42 (01) ◽  
pp. 295-301 ◽  
Author(s):  
Nadine Guillotin-Plantard

We consider a random walker on ad-regular graph. Starting from a fixed vertex, the first step is a unit step in any one of theddirections, with common probability 1/dfor each one. At any later step, the random walker moves in any one of the directions, with probabilityqfor a reversal of direction and probabilitypfor any other direction. This model was introduced and first studied by Gillis (1955), in the case when the graph is ad-dimensional square lattice. We prove that the Gillis random walk on ad-regular graph is recurrent if and only if the simple random walk on the graph is recurrent. The Green function of the Gillis random walk will be also given, in terms of that of the simple random walk.


1975 ◽  
Vol 12 (03) ◽  
pp. 466-476
Author(s):  
V. Barnett

Prompted by a rivulet model for the flow of liquid through packed columns we consider a simple random walk on parallel axes moving at different rates. A particle may make one of three transitions at each time instant: to the right or to the left on the axis it was on at the previous time instant, or across to the other axis. Results are obtained for the unrestricted walk, and for the walk with absorbing, or reflecting, end-points.


2016 ◽  
Vol 8 (6) ◽  
pp. 128
Author(s):  
Yao Elikem Ayekple ◽  
Derrick Asamoah Owusu ◽  
Nana Kena Frempong ◽  
Prince Kwaku Fefemwole

The simple random walk with mixed barriers at state $ 0 $ and state $ n $ defined on non-negative integers has transition matrix $ P $ with transition probabilities $ p_{ij} $. Matrix $ Q $ is obtained from matrix $ P $ when rows and columns at state $ 0 $ and state $ n $ are deleted . The fundamental matrix $ B $ is the inverse of the matrix $ A = I -Q $, where $ I $ is an identity matrix. The expected reflecting and absorbing time and reflecting and absorbing probabilities can be easily deduced once $ B $ is known. The fundamental matrix can thus be used to calculate the expected times and probabilities of NCD's.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Karl K. Sabelfeld ◽  
Dmitrii Smirnov

Abstract We suggest in this paper a global random walk on grid (GRWG) method for solving second order elliptic equations. The equation may have constant or variable coefficients. The GRWS method calculates the solution in any desired family of m prescribed points of the gird in contrast to the classical stochastic differential equation based Feynman–Kac formula, and the conventional random walk on spheres (RWS) algorithm as well. The method uses only N trajectories instead of mN trajectories in the RWS algorithm and the Feynman–Kac formula. The idea is based on the symmetry property of the Green function and a double randomization approach.


10.37236/4106 ◽  
2014 ◽  
Vol 21 (4) ◽  
Author(s):  
Bernhard A. Moser

Two different elementary approaches for deriving an explicit formula for the distribution of the range of a simple random walk on $\mathbb{Z}$ of length $n$ are presented. Both of them rely on Hermann Weyl's discrepancy norm, which equals the maximal partial sum of the elements of a sequence. By this the original combinatorial problem on $\mathbb{Z}$ can be turned into a known path-enumeration problem on a bounded lattice. The solution is provided by means of the adjacency matrix $\mathbf Q_d$ of the walk on a bounded lattice $(0,1,\ldots,d)$. The second approach is algebraic in nature, and starts with the adjacency matrix $\mathbf{Q_d}$. The powers of the adjacency matrix are expanded in terms of products of non-commutative left and right shift matrices. The representation of such products by means of the discrepancy norm reveals the solution directly.


1975 ◽  
Vol 12 (3) ◽  
pp. 466-476 ◽  
Author(s):  
V. Barnett

Prompted by a rivulet model for the flow of liquid through packed columns we consider a simple random walk on parallel axes moving at different rates. A particle may make one of three transitions at each time instant: to the right or to the left on the axis it was on at the previous time instant, or across to the other axis. Results are obtained for the unrestricted walk, and for the walk with absorbing, or reflecting, end-points.


Author(s):  
Aiping Wang ◽  
Jerry Ridenhour ◽  
Anton Zettl

The Green function of singular limit-circle problems is constructed directly for the problem, not as a limit of sequences of regular Green's functions. This construction is used to obtain adjointness and self-adjointness conditions which are entirely analogous to the regular case. As an application, a new and explicit formula for the Green function of the classical Legendre problem is found.


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