Martingale approach for first-passage problems of time-additive observables in Markov processes

Abstract: We develop a method based on martingales to study first-passage problems of time-additive observables exiting an interval of finite width in a Markov process. In the limit that the interval width is large, we derive generic expressions for the splitting probability and the cumulants of the first-passage time. These expressions relate first-passage quantities to the large deviation properties of the time-additive observable. We find that there are three qualitatively different regimes depending on the properties of the large deviation rate function of the time-additive observable. These regimes correspond to exponential, super-exponential, or sub-exponential suppression of events at the unlikely boundary of the interval. Furthermore, we show that the statistics of first-passage times at both interval boundaries are in general different, even for symmetric thresholds and in the limit of large interval widths. While the statistics of the times to reach the likely boundary are determined by the cumulants of the time-additive observables in the original process, those at the unlikely boundary are determined by a dual process. We obtain these results from a one-parameter family of positive martingales that we call Perron martingales, as these are related to the Perron root of a tilted version of the transition rate matrix defining the Markov process. Furthermore, we show that each eigenpair of the tilted matrix has a one-parameter family of martingales. To solve first-passage problems at finite thresholds, we generally require all one-parameter families of martingales, including the non-positive ones. We illustrate this by solving the first-passage problem for run-and-tumble particles exiting an interval of finite width.