Diversity of Sharp Restart
arXiv:2207.09200 · doi:10.1088/1751-8121/acb184
Abstract
When applied to a stochastic process of interest, a restart protocol alters the overall statistical distribution of the process' completion time; thus, the completion-time's mean and randomness change. The explicit effect of restart on the mean is well understood, and it is known that: from a mean perspective, deterministic restart protocols -- termed sharp restart -- can out-perform any other restart protocol. However, little is known on the explicit effect of restart on randomness. This paper is the second in a duo exploring the effect of sharp restart on randomness: via a Boltzmann-Gibbs-Shannon entropy analysis in the first part, and via a diversity analysis in this part. Specifically, gauging randomness via diversity -- a measure that is intimately related to the Renyi entropy -- this paper establishes a set of universal criteria that determine: A) precisely when a sharp-restart protocol decreases/increases the diversity of completion times; B) the very existence of sharp-restart protocols that decrease/increase the diversity of completion times. Moreover, addressing jointly mean-behavior and randomness, this paper asserts and demonstrates when sharp restart has an aligned effect on the two (decreasing/increasing both), and when the effect is antithetical (decreasing one while increasing the other). The joint mean-diversity results require remarkably little information regarding the (original) statistical distributions of completion times, and are remarkably practical and easy to implement.
References in corpus (9)
- Power-law distributions in empirical data
- First Passage Under Restart
- First order transition for the optimal search time of Lévy flights with resetting
- Optimal mean first-passage time for a Brownian searcher subjected to resetting: experimental and theoretical results
- Stochastic Search with Poisson and Deterministic Resetting
- Restart expedites quantum walk hitting times
- Mitigating long queues and waiting times with service resetting
- Diffusion processes with Gamma-distributed resetting and non-instantaneous returns
- Stochastic resetting in the Kramers problem: A Monte Carlo approach