Continuous-time random walk

In mathematics, a continuous-time random walk (CTRW) is a generalization of a random walk where the wandering particle waits for a random time between jumps. It is a stochastic jump process with arbitrary distributions of jump lengths and waiting times.[1][2][3] More generally it can be seen to be a special case of a Markov renewal process.

Motivation edit

CTRW was introduced by Montroll and Weiss[4] as a generalization of physical diffusion processes to effectively describe anomalous diffusion, i.e., the super- and sub-diffusive cases. An equivalent formulation of the CTRW is given by generalized master equations.[5] A connection between CTRWs and diffusion equations with fractional time derivatives has been established.[6] Similarly, time-space fractional diffusion equations can be considered as CTRWs with continuously distributed jumps or continuum approximations of CTRWs on lattices.[7]

Formulation edit

A simple formulation of a CTRW is to consider the stochastic process   defined by

 

whose increments   are iid random variables taking values in a domain   and   is the number of jumps in the interval  . The probability for the process taking the value   at time   is then given by

 

Here   is the probability for the process taking the value   after   jumps, and   is the probability of having   jumps after time  .

Montroll–Weiss formula edit

We denote by   the waiting time in between two jumps of   and by   its distribution. The Laplace transform of   is defined by

 

Similarly, the characteristic function of the jump distribution   is given by its Fourier transform:

 

One can show that the Laplace–Fourier transform of the probability   is given by

 

The above is called the MontrollWeiss formula.

Examples edit

References edit

  1. ^ Klages, Rainer; Radons, Guenther; Sokolov, Igor M. (2008-09-08). Anomalous Transport: Foundations and Applications. ISBN 9783527622986.
  2. ^ Paul, Wolfgang; Baschnagel, Jörg (2013-07-11). Stochastic Processes: From Physics to Finance. Springer Science & Business Media. pp. 72–. ISBN 9783319003276. Retrieved 25 July 2014.
  3. ^ Slanina, Frantisek (2013-12-05). Essentials of Econophysics Modelling. OUP Oxford. pp. 89–. ISBN 9780191009075. Retrieved 25 July 2014.
  4. ^ Elliott W. Montroll; George H. Weiss (1965). "Random Walks on Lattices. II". J. Math. Phys. 6 (2): 167. Bibcode:1965JMP.....6..167M. doi:10.1063/1.1704269.
  5. ^ . M. Kenkre; E. W. Montroll; M. F. Shlesinger (1973). "Generalized master equations for continuous-time random walks". Journal of Statistical Physics. 9 (1): 45–50. Bibcode:1973JSP.....9...45K. doi:10.1007/BF01016796.
  6. ^ Hilfer, R.; Anton, L. (1995). "Fractional master equations and fractal time random walks". Phys. Rev. E. 51 (2): R848–R851. Bibcode:1995PhRvE..51..848H. doi:10.1103/PhysRevE.51.R848.
  7. ^ Gorenflo, Rudolf; Mainardi, Francesco; Vivoli, Alessandro (2005). "Continuous-time random walk and parametric subordination in fractional diffusion". Chaos, Solitons & Fractals. 34 (1): 87–103. arXiv:cond-mat/0701126. Bibcode:2007CSF....34...87G. doi:10.1016/j.chaos.2007.01.052.