Computational complexity of uniform quantum circuit families and quantum Turing machines Communicated by O. Watanabe

H Nishimura, M Ozawa - Theoretical Computer Science, 2002 - Elsevier
H Nishimura, M Ozawa
Theoretical Computer Science, 2002Elsevier
Deutsch proposed two sorts of models of quantum computers, quantum Turing machines
(QTMs) and quantum circuit families (QCFs). In this paper we explore the computational
powers of these models and re-examine the claim of the computational equivalence of these
models often made in the literature without detailed investigations. For this purpose, we
formulate the notion of the codes of QCFs and the uniformity of QCFs by the computability of
the codes. Various complexity classes are introduced for QTMs and QCFs according to …
Deutsch proposed two sorts of models of quantum computers, quantum Turing machines (QTMs) and quantum circuit families (QCFs). In this paper we explore the computational powers of these models and re-examine the claim of the computational equivalence of these models often made in the literature without detailed investigations. For this purpose, we formulate the notion of the codes of QCFs and the uniformity of QCFs by the computability of the codes. Various complexity classes are introduced for QTMs and QCFs according to constraints on the error probability of algorithms or transition amplitudes. Their interrelations are examined in detail. For Monte Carlo algorithms, it is proved that the complexity classes based on uniform QCFs are identical with the corresponding classes based on QTMs. However, for Las Vegas algorithms, it is still open whether the two models are equivalent. We indicate the possibility that they are not equivalent. In addition, we give a complete proof of the existence of a universal QTM efficiently simulating multi-tape QTMs. We also examine the simulation of various types of QTMs such as multi-tape QTMs, single tape QTMs, stationary, normal form QTMs (SNQTMs), and QTMs with the binary tapes. As a result, we show that these QTMs are computationally equivalent to one another as computing models implementing not only Monte Carlo algorithms but also exact (or error-free) ones.
Elsevier