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数理解析研究所講究録

Factoring Algorithms Based on NMR Quantum Computers (Computer Algebra : Algorithms, Implementations and Applications)

Noboru Kunihiro, Shigeru Yamashita

Published Nov 1, 2002• 1 citation
OpenAlex

Abstract

No polynomial time algorithms have been proposed for the factoring and discrete logarithm problems.However, Shor showed that these problems can be solved by aquantum Turing machine in 1994.Sev- eral devices have been proposed toward the realization of quantum computers.Among them, the NMR quantum computer seems to be the nearest to the target goal.Since the NMR quantum computer has different features from ordinary ones, we cannot directly implement Shor's algorithms.In this paper, we propose new simple algorithms that work on NMR quantum computers to solve the factoring and discrete logarithm problems.

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No polynomial time algorithms have been proposed for the factoring and discrete logarithm problems.However, Shor showed that these problems can be solved by aquantum Turing machine in 1994.Sev- eral devices have been proposed toward the realization of quantum computers.Among them, the NMR quantum computer seems to be the nearest to the target goal.Since the NMR quantum computer has different features from ordinary ones, we cannot directly implement Shor's algorithms.In this paper, we propose new simple algorithms that work on NMR quantum computers to solve the factoring and discrete logarithm problems.
In 1985, David Deutsch introduced quantum Turing machines (QTMs for short) as Turing machines which can perform so called quantum parallel computations. Algorithms executed on QTMs are called quantum algorithms. It is well known that Peter Shor designed a polynomial time quantum algorithm for integer factoring in 1994. In this paper, we first illustrate several major methods of designing efficient quantum algorithms with Shor's algorithm as an example. On the other hand, many researchers are studying how to physically implement quantum computers based on QTM. Among others, NMR (Nuclear Magnetic Resonance) offers an appealing prospect for implementation of quantum computers because of a number of reasons. But, quantum computations performed on NMR is slightly different from those performed on QTMs. For example, Shor's factoring algorithm cannot be executed on an NMR quantum computer as it is. In this paper, we show how to factor integers in polynomial time by using NMR quantum computers.
A digital computer is generally believed to be an efficient universal computing device; that is, it is believed to be able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. This paper considers factoring integers and finding discrete logarithms, two problems that are generally thought to be hard on classical computers and that have been used as the basis of several proposed cryptosystems. Efficient randomized algorithms are given for these two problems on a hypothetical quantum computer. These algorithms take a number of steps polynomial in the input size, for example, the number of digits of the integer to be factored.
A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time by at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. This paper considers factoring integers and finding discrete logarithms, two problems which are generally thought to be hard on a classical computer and which have been used as the basis of several proposed cryptosystems. Efficient randomized algorithms are given for these two problems on a hypothetical quantum computer. These algorithms take a number of steps polynomial in the input size, e.g., the number of digits of the integer to be factored.
We show in some detail how to implement Shor's efficient quantum algorithm for discrete logarithms for the particular case of elliptic curve groups. It turns out that for this problem a smaller quantum computer can solve problems further beyond current computing than for integer factorisation. A 160 bit elliptic curve cryptographic key could be broken on a quantum computer using around 1000 qubits while factoring the security-wise equivalent 1024 bit RSA modulus would require about 2000 qubits. In this paper we only consider elliptic curves over GF(p) and not yet the equally important ones over GF(2^n) or other finite fields. The main technical difficulty is to implement Euclid's gcd algorithm to compute multiplicative inverses modulo p. As the runtime of Euclid's algorithm depends on the input, one difficulty encountered is the ``quantum halting problem''.
A computer is generally considered to be a universal computational device; i.e., it is believed able to simulate any physical computational device with a cost in computation time of at most a polynomial factor: It is not clear whether this is still true when quantum mechanics is taken into consideration. Several researchers, starting with David Deutsch, have developed models for quantum mechanical computers and have investigated their computational properties. This paper gives Las Vegas algorithms for finding discrete logarithms and factoring integers on a quantum computer that take a number of steps which is polynomial in the input size, e.g., the number of digits of the integer to be factored. These two problems are generally considered hard on a classical computer and have been used as the basis of several proposed cryptosystems. We thus give the first examples of quantum cryptanalysis.>