  The theory of stochastic resetting asserts that restarting a search process
at certain times may accelerate the finding of a target. In the case of a
classical diffusing particle trapped in a potential well, stochastic resetting
may decrease the escape times due to thermal fluctuations. Here, we numerically
explore the Kramers problem for a cubic potential, which is the simplest
potential with a escape. Both deterministic and Poisson resetting times are
analyzed. We use a Monte Carlo approach, which is necessary for generic complex
potentials, and we show that the optimal rate is related to the escape times
distribution in the case without resetting. Furthermore, we find rates for
which resetting is beneficial even if the resetting position is located on the
contrary side of the escape.
