Abstract

Abstract We provide a uniform framework to compute the exact distribution of the number of minima/maxima in three different random walk landscape models in one dimension. The landscape is generated by the trajectory of a discrete-time continuous space random walk with arbitrary symmetric and continuous jump distribution at each step. In model I, we consider a ``free'' random walk of $N$ steps. In model II, we consider a ``meander landscape'' where the random walk, starting at the origin, stays non-negative up to $N$ steps. In model III, we study a ``first-passage landscape'' which is generated by the trajectory of a random walk that starts at the origin and stops when it crosses the origin for the first time. 
We demonstrate that while the exact distribution of the number of minima is different in the three models, for each model it is universal for all $N$, in the sense that it does not depend on the jump distribution as long as it is symmetric and continuous. In the last two cases we show that this universality follows from a non trivial mapping to the Sparre Andersen theorem known for the first-passage probability of discrete-time random walks with symmetric and continuous jump distribution. Our analytical results are in excellent agreement with our numerical simulations.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.