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Stochastically switching force terms appear frequently in models ofbiological systems under the action of active agents such as proteins. Theinteraction of switching force and Brownian motion can create an "effectivethermal equilibrium" even though the system does not obey a potential function.In order to extend the field of energy landscape analysis to understandstability and transitions in switching systems, we derive the quasipotentialthat defines this effective equilibrium for a general overdamped Langevinsystem with a force switching according to a continuous-time Markov chainprocess. Combined with the string method for computing most-probable transitionpaths, we apply our method to an idealized system and show the appearance ofpreviously unreported numerical challenges. We present modifications to thealgorithms to overcome these challenges, and show validity by demonstratingagreement between our computed quasipotential barrier and asymptotic MonteCarlo transition times in the system.

Numerical computation of effective thermal equilibrium in Stochastically Switching Langevin Systems