Entropy of sharp restart

Abstract Restart has the potential of expediting or impeding completion times general random processes. Consequently, issue mean-performance takes center stage: quantifying how application restart on a process interest impacts its completion-time’s mean. Going beyond mean, little is known affects stochasticity measures time. This paper first in duo studies that address this knowledge gap via: comprehensive analysis quantifies sharp restart—a keystone protocol—impacts Shannon entropy The establishes closed-form results for with timers, fast timers (high-frequency resetting), and slow (low-frequency resetting). These share common structure: comparing hazard rate to flat benchmark—the constant an exponential distribution whose equal entropy. In addition, using information-geometric approach based Kullback–Leibler distances, determine very existence which decreases increases Our work sheds light intricate interplay between randomness—as gauged by