Exact closed-form recurrence probabilities for biased random walks at any step number
Debendro Mookerjee, Sarah Kostinski

TL;DR
This paper derives exact closed-form formulas for the survival and last return probabilities of biased 1D random walks at any step, revealing how bias influences recurrence behavior and applicable to molecular motor models.
Contribution
It provides the first exact formulas for biased walk recurrence probabilities at any step, including intermediate ranges, and analyzes the impact of bias on last return decay.
Findings
Exact survival probability formula valid for any step number.
Critical bias value where last return probability behavior changes.
Saturation of critical bias at 1/√3 for infinite walks.
Abstract
We report on a closed-form expression for the survival probability of a discrete 1D biased random walk to not return to its origin after N steps. Our expression is exact for any N, including the elusive intermediate range, thereby allowing one to study its convergence to the large N limit. In that limit we recover Polya's recurrence probability, i.e. the survival probability equals the magnitude of the bias. We then obtain a closed-form expression for the probability of last return. In contrast to the bimodal behavior for the unbiased case, we show that the probability of last return decays monotonically throughout the walk beyond a critical bias. We obtain a simple expression for the critical bias as a function of the walk length, and show that it saturates at for infinitely long walks. This property is missed when using expressions developed for the large N limit.…
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Taxonomy
TopicsStochastic processes and statistical mechanics · DNA and Biological Computing · Algorithms and Data Compression
