We are studying the motion of a random walker in generalised d-dimensional
continuum with unit step length (up to 10 dimensions) and its projected one
dimensional motion numerically. The motion of a random walker in lattice or
continuum is well studied in statistical physics but what will be the statistics of
projected one dimensional motion of higher dimensional random walker is
yet to be explored. Here in this paper, by addressing this particular type of
problem, it shows that the projected motion is diffusive irrespective of any
dimension; however, the diffusion rate is changing inversely with dimensions.
As a consequence, it can be predicted that for the one dimensional projected
motion of infinite dimensional random walk, the diffusion rate will be zero.
This is an interesting result, at least pedagogically, which implies that though
in infinite dimensions there is diffusion, its one dimensional projection is motionless.
At the end of the discussion we are able to make a good comparison
between projected one dimensional motion of generalised d-dimensional
random walk with unit step length and pure one dimensional random walk
with random step length varying uniformly between -h to h where h is a “step
length renormalizing factor”.
References
[1]
Codling, E.A., Plank, M.J. and Benhamou, S. (2008) Random Walk Models in Biology. Journal of the Royal Society Interface, 5, 813-834.
[2]
Freund, J.A. and P?schel, T. (2000) Stochastic Processes in Physics, Chemistry, and Biology (Lecture Notes in Physics). Springer, Berlin.
[3]
Bhattacherjee, S.M., Giacometti, A. and Maritan, A. (2013) Flory Theory for Polymers. Journal of Physics: Condensed Matter, 25, Article ID: 503101.
[4]
Hsu, H.-P. and Grassberger, P. (2011) A Review of Monte Carlo Simulations of Polymers with PERM. Journal of Statistical Physics, 144, 597.
https://doi.org/10.1007/s10955-011-0268-x
[5]
Redner, S. (2001) A Guide to First-Passage Processes. Cambridge University Press, Cambridge. https://doi.org/10.1017/CBO9780511606014
[6]
Lubeck, S. and Hucht, A. (2001) Absorbing Phase Transition in a Conserved Lattice Gas with Random Neighbour Particle Hopping. Journal of Physics A: Mathematical and Theoretical, 34, L577. https://doi.org/10.1088/0305-4470/34/42/103
[7]
Sumedha and Dhar, D. (2006) Quenched Averages for Self-Avoiding Walks and Polygons on Deterministic Fractals. Journal of Statistical Physics, 125, 55-76.
https://doi.org/10.1007/s10955-006-9098-7
[8]
Phillips, R., et al. (2013) Physical Biology of the Cell. 2nd Edition, Garland Science, London, New York.
[9]
Serino, C.A. and Redner, S. (2010) The Pearson Walk with Shrinking Steps in Two Dimensions. Journal of Statistical Mechanics: Theory and Experiment, 2010, P01006. https://doi.org/10.1088/1742-5468/2010/01/P01006
[10]
Acharyya, M. (2015) Model and Statistical Analysis of the Motion of a Tired Random Walker in Continuum. Journal of Modern Physics, 6, 2021-2034.
https://doi.org/10.4236/jmp.2015.614208
[11]
Acharyya, A.B. (2015) Return Probability of a Random Walker in Continuum with Uniformly Distributed Jump-Length. arXiv:1506.00269.
[12]
Pearson, K. (1905) The Problem of the Random Walk. Nature, 72, 294.
[13]
Rayleigh, L. (1919) On the Problem of Random Vibrations, and of Random Flights in One, Two, or Three Dimensions. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 37, 321-347.
[14]
Watson, G.N. (1941) A Treatise on the Theory of Bessel Functions. 2nd Edition, Cambridge University Press, Cambridge.
[15]
Borwein, J.M., Straub, A. and Vignat, C. (2015) Densities of Short Uniform Random Walks in Higher Dimensions. arXiv:1508.04729.
[16]
Mattingly, J.C., Pillai, N.S. and Stuart, A.M. (2012) Diffusion Limits of the Random Walk Metropolish Algorithm in High Dimensions. The Annals of Applied Probability, 22, 881-930. https://doi.org/10.1214/10-AAP754
[17]
Poyla, G. (1921) über eine Aufgabe der Wahrscheinlichkeitsrechnung betreffend die Irrfahrt im Stra?ennetz. Mathematische Annalen, 84, 149-160.
https://doi.org/10.1007/BF01458701
[18]
Abramov, V.M. (2016) Eventual Return Probability in Multidimensional Random Walks. arXiv:1601.02297.
[19]
Ioffe, D. (2014) Multidimensional Random Polymers: A Renewal Approach. arXiv:1412.0229.
[20]
Kavraki, L.E., Svestka, P., Latmbe, J.-C. and Overmans, M.H. (1996) Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces. IEEE Transaction on Robotics and Automation, 12, 566-580.
https://doi.org/10.1109/70.508439
[21]
Boguna, M., Porra, J.M. and Masoliver, J. (1998) Generalization of the Persistent Random Walk to Dimensions Greater than 1. Physical Review E, 58, Article ID: 6992. https://doi.org/10.1103/PhysRevE.58.6992