Target search optimization by threshold resetting

Abstract

We introduce a new class of first passage time optimization mediated by a threshold resetting (TR) mechanism. Inspired by many natural processes that operate under “safety covenant” or are governed by “threshold triggered events” wherein a system, structure, or process exceeds a predefined limit (threshold), causing failure, degradation, or a transition to a different state; we consider an arbitrary first passage process that is intermittently renewed when the search agents, looking for targets, are simultaneously reset upon reaching a certain threshold. Unlike the classical paradigm where the resetting events are externally modulated, here they are event driven and thus, strongly coupled to the system variables. Furthermore, the simultaneous resetting induces long-range interactions between the searchers. A unified theoretical framework is presented for computing the search time associated with this class of correlated stochastic processes, further showcasing a rich and diverse optimization phenomena.