Probabilistic rebound Turing machines
This paper introduces a probabilistic rebound Turing machine (PRTM), and investigates the fundamental property of the machine. We first prove a sublogarithmic lower space bound on the space complexity of this model with bounded errors for recognizing specific languages. This lower bound strengthens a previous lower bound for conventional probabilistic Turing machines with bounded errors. We then show, by using our lower space bound and an idea in the proof of it, that
probabilistic rebound turing machine rebound automaton space hierarchy closure property