49 research outputs found

    Succinctness of two-way probabilistic and quantum finite automata

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    We prove that two-way probabilistic and quantum finite automata (2PFA's and 2QFA's) can be considerably more concise than both their one-way versions (1PFA's and 1QFA's), and two-way nondeterministic finite automata (2NFA's). For this purpose, we demonstrate several infinite families of regular languages which can be recognized with some fixed probability greater than 1/2 {1/2} by just tuning the transition amplitudes of a 2QFA (and, in one case, a 2PFA) with a constant number of states, whereas the sizes of the corresponding 1PFA's, 1QFA's and 2NFA's grow without bound. We also show that 2QFA's with mixed states can support highly efficient probability amplification. The weakest known model of computation where quantum computers recognize more languages with bounded error than their classical counterparts is introduced.Comment: A new version, 21 pages, late

    Proving the power of postselection

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    It is a widely believed, though unproven, conjecture that the capability of postselection increases the language recognition power of both probabilistic and quantum polynomial-time computers. It is also unknown whether polynomial-time quantum machines with postselection are more powerful than their probabilistic counterparts with the same resource restrictions. We approach these problems by imposing additional constraints on the resources to be used by the computer, and are able to prove for the first time that postselection does augment the computational power of both classical and quantum computers, and that quantum does outperform probabilistic in this context, under simultaneous time and space bounds in a certain range. We also look at postselected versions of space-bounded classes, as well as those corresponding to error-free and one-sided error recognition, and provide classical characterizations. It is shown that NL\mathsf{NL} would equal RL\mathsf{RL} if the randomized machines had the postselection capability.Comment: 26 pages. This is a heavily improved version of arXiv:1102.066
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