1,475 research outputs found
Bounded Counter Languages
We show that deterministic finite automata equipped with two-way heads
are equivalent to deterministic machines with a single two-way input head and
linearly bounded counters if the accepted language is strictly bounded,
i.e., a subset of for a fixed sequence of symbols . Then we investigate linear speed-up for counter machines. Lower
and upper time bounds for concrete recognition problems are shown, implying
that in general linear speed-up does not hold for counter machines. For bounded
languages we develop a technique for speeding up computations by any constant
factor at the expense of adding a fixed number of counters
State succinctness of two-way finite automata with quantum and classical states
{\it Two-way quantum automata with quantum and classical states} (2QCFA) were
introduced by Ambainis and Watrous in 2002. In this paper we study state
succinctness of 2QCFA.
For any and any , we show that:
{enumerate} there is a promise problem which can be solved by a
2QCFA with one-sided error in a polynomial expected running time
with a constant number (that depends neither on nor on ) of
quantum states and classical states,
whereas the sizes of the corresponding {\it deterministic finite automata}
(DFA), {\it two-way nondeterministic finite automata} (2NFA) and polynomial
expected running time {\it two-way probabilistic finite automata} (2PFA) are at
least , , and , respectively; there
exists a language over the alphabet
which can be recognized by a 2QCFA with one-sided error
in an exponential expected running time with a constant number of
quantum states and classical states,
whereas the sizes of the corresponding DFA, 2NFA and polynomial expected
running time 2PFA are at least , , and ,
respectively; {enumerate} where is a constant.Comment: 26pages, comments and suggestions are welcom
Learning Quantum Finite Automata with Queries
{\it Learning finite automata} (termed as {\it model learning}) has become an
important field in machine learning and has been useful realistic applications.
Quantum finite automata (QFA) are simple models of quantum computers with
finite memory. Due to their simplicity, QFA have well physical realizability,
but one-way QFA still have essential advantages over classical finite automata
with regard to state complexity (two-way QFA are more powerful than classical
finite automata in computation ability as well). As a different problem in {\it
quantum learning theory} and {\it quantum machine learning}, in this paper, our
purpose is to initiate the study of {\it learning QFA with queries} (naturally
it may be termed as {\it quantum model learning}), and the main results are
regarding learning two basic one-way QFA: (1) We propose a learning algorithm
for measure-once one-way QFA (MO-1QFA) with query complexity of polynomial
time; (2) We propose a learning algorithm for measure-many one-way QFA
(MM-1QFA) with query complexity of polynomial-time, as well.Comment: 18pages; comments are welcom
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