In this chapter we review some of the recent developments for efficient estimation of rare-
events, most of which involve application of importance sampling techniques to achieve …

We consider the problem of conditioning a Markov process on a rare event and of
representing this conditioned process by a conditioning-free process, called the effective or …

This paper surveys recent techniques that have been developed for rare-event analysis of
stochastic systems via simulation. We review standard (state-independent) techniques that …

Very often when studying non-equilibrium systems one is interested in analysing dynamical
behaviour that occurs with very low probability, so called rare events. In practice, since rare …

We have shown recently that a Markov process conditioned on rare events involving time-
integrated random variables can be described in the long-time limit by an effective Markov …

Recent work has shown the effectiveness of tensor network methods for computing large
deviation functions in constrained stochastic models in the infinite time limit. Here we show …

We present a systematic analysis of stochastic processes conditioned on an empirical
observable Q_T QT defined in a time interval 0, T, for large T. We build our analysis starting …

We use projected entangled-pair states (PEPS) to calculate the large deviation statistics of
the dynamical activity of the two-dimensional East model, and the two-dimensional …

We introduce and test an algorithm that adaptively estimates large deviation functions
characterizing the fluctuations of additive functionals of Markov processes in the long-time …

We present a method to probe rare molecular dynamics trajectories directly using
reinforcement learning. We consider trajectories that are conditioned to transition between …