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Theoretical Computer Science

On the simulation of quantum turing machines

Marco Carpentieri

Published Mar 26, 2003• 7 citations
Publisher
DOI
10.1016/s0304-3975(03)00054-9

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It is reasonable to assume that quantum computations take place under the control of the classical world. For modelling this standard situation, we introduce a Classically controlled Quantum Turing Machine (CQTM), which is a Turing machine with a quantum tape for acting on quantum data, and a classical transition function for formalised classical control. In a CQTM, unitary transformations and quantum measurements are allowed. We show that any classical Turing machine can be simulated by a CQTM without loss of efficiency. Furthermore, we show that any -tape CQTM can be simulated by a 2-tape CQTM with a quadratic loss of efficiency. In order to compare CQTMs with existing models of quantum computation, we prove that any uniform family of quantum circuits (Yao 1993) is efficiently approximated by a CQTM. Moreover, we prove that any semi-uniform family of quantum circuits (Nishimura and Ozawa 2002), and any measurement calculus pattern (Danos et al. 2004) are efficiently simulated by a CQTM. Finally, we introduce a Measurement-based Quantum Turing Machine (MQTM), which is a restriction of CQTMs in which only projective measurements are allowed. We prove that any CQTM is efficiently simulated by a MQTM. In order to appreciate the similarity between programming classical Turing machines and programming CQTMs, some examples of CQTMs are given.

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Simulations of Quantum Turing Machines by Quantum Multi-Stack Machines

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As was well known, in classical computation, Turing machines, circuits, multi-stack machines, and multi-counter machines are equivalent, that is, they can simulate each other in polynomial time. In quantum computation, Yao [11] first proved that for any quantum Turing machines $M$, there exists quantum Boolean circuit $(n,t)$-simulating $M$, where $n$ denotes the length of input strings, and $t$ is the number of move steps before machine stopping. However, the simulations of quantum Turing machines by quantum multi-stack machines and quantum multi-counter machines have not been considered, and quantum multi-stack machines have not been established, either. Though quantum counter machines were dealt with by Kravtsev [6] and Yamasaki {\it et al.} [10], in which the machines count with $0,\pm 1$ only, we sense that it is difficult to simulate quantum Turing machines in terms of this fashion of quantum computing devices, and we therefore prove that the quantum multi-counter machines allowed to count with $0,\pm 1,\pm 2,...,\pm n$ for some $n>1$ can efficiently simulate quantum Turing machines. Therefore, our mail goals are to establish quantum multi-stack machines and quantum multi-counter machines with counts $0,\pm 1,\pm 2,...,\pm n$ and $n>1$, and particularly to simulate quantum Turing machines by these quantum computing devices.

arXiv:quant-ph/0501176•Jan 30, 2005•3 citations

Halting of Quantum Turing Machines

Masanao Ozawa

Lecture notes in computer science•Jan 1, 2002•7 citations
It is reasonable to assume that quantum computations take place under the control of the classical world. For modelling this standard situation, we introduce a Classically controlled Quantum Turing Machine (CQTM), which is a Turing machine with a quantum tape for acting on quantum data, and a classical transition function for formalised classical control. In a CQTM, unitary transformations and quantum measurements are allowed. We show that any classical Turing machine can be simulated by a CQTM without loss of efficiency. Furthermore, we show that any -tape CQTM can be simulated by a 2-tape CQTM with a quadratic loss of efficiency. In order to compare CQTMs with existing models of quantum computation, we prove that any uniform family of quantum circuits (Yao 1993) is efficiently approximated by a CQTM. Moreover, we prove that any semi-uniform family of quantum circuits (Nishimura and Ozawa 2002), and any measurement calculus pattern (Danos et al. 2004) are efficiently simulated by a CQTM. Finally, we introduce a Measurement-based Quantum Turing Machine (MQTM), which is a restriction of CQTMs in which only projective measurements are allowed. We prove that any CQTM is efficiently simulated by a MQTM. In order to appreciate the similarity between programming classical Turing machines and programming CQTMs, some examples of CQTMs are given.
As was well known, in classical computation, Turing machines, circuits, multi-stack machines, and multi-counter machines are equivalent, that is, they can simulate each other in polynomial time. In quantum computation, Yao [11] first proved that for any quantum Turing machines MMM, there exists quantum Boolean circuit (n,t)(n,t)(n,t)-simulating MMM, where nnn denotes the length of input strings, and ttt is the number of move steps before machine stopping. However, the simulations of quantum Turing machines by quantum multi-stack machines and quantum multi-counter machines have not been considered, and quantum multi-stack machines have not been established, either. Though quantum counter machines were dealt with by Kravtsev [6] and Yamasaki {\it et al.} [10], in which the machines count with 0,±10,\pm 10,±1 only, we sense that it is difficult to simulate quantum Turing machines in terms of this fashion of quantum computing devices, and we therefore prove that the quantum multi-counter machines allowed to count with 0,±1,±2,...,±n0,\pm 1,\pm 2,...,\pm n0,±1,±2,...,±n for some n>1n>1n>1 can efficiently simulate quantum Turing machines. Therefore, our mail goals are to establish quantum multi-stack machines and quantum multi-counter machines with counts 0,±1,±2,...,±n0,\pm 1,\pm 2,...,\pm n0,±1,±2,...,±n and n>1n>1n>1, and particularly to simulate quantum Turing machines by these quantum computing devices.