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Shors Algorithm Using Efficient Approximate Quantum Fourier Transform

Kento Oonishi, Kunihiro Noboru

Published Sep 25, 2023• 0 citations
OpenAlex

Abstract

Shor's algorithm solves the integer factoring and discrete logarithm problems in polynomial time. Therefore, the evaluation of Shor's algorithm is essential for evaluating the security of currently used public-key cryptosystems because the integer factoring and discrete logarithm problems are crucial for the security of these cryptosystems. In this article, a new approximate quantum Fourier transform is proposed, and it is applied to Rines and Chuang's implementation. The proposed implementation requires one-third the number of T gates of the original. Moreover, it requires one-fourth of the T-depth of the original. Finally, a T-scheduling method for running the circuit with the smallest KQ (where K is the number of logical qubits and Q is the circuit depth) is presented.

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Shor's Algorithm Using Efficient Approximate Quantum Fourier Transform

Kento Oonishi, Noboru Kunihiro

Shor's algorithm solves the integer factoring and discrete logarithm problems in polynomial time. Therefore, the evaluation of Shor's algorithm is essential for evaluating the security of currently used public-key cryptosystems because the integer factoring and discrete logarithm problems are crucial for the security of these cryptosystems. In this article, a new approximate quantum Fourier transform is proposed, and it is applied to Rines and Chuang's implementation. The proposed implementation requires one-third the number of$T$gates of the original. Moreover, it requires one-fourth the$T$-depth of the original. Finally, a$T$-scheduling method for running the circuit with the smallest KQ is presented.

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Shor’s algorithm is a quantum algorithm that can efficiently solve the problems of integer factorization and discrete logarithms, which potentially break currently used public-key cryptosystems such as RSA and elliptic curve cryptography. However, a significant challenge in solving these problems is the noise inherent in quantum computers. Previous research advanced fault-tolerant techniques such as surface codes to mitigate this noise in quantum computers. Analyzing the security of currently used public-key cryptosystems on fault-tolerant quantum computers is essential. In this paper, we estimate the computational cost required to solve integer factorization using Shor’s algorithm on surface codes. We evaluated computational resources required for surface codes and magic state distillation and derived the computational cost of Shor’s algorithm based on these evaluations. Our computational complexity analysis indicates that there is no significant difference in the order of complexity. However, it underscores the paramount importance of optimizing the coefficient part for future efficiency improvements.

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The emergence of some quantum algorithms has brought a serious threat to modern cryptography,among which Shor’s algorithm is the most important threatening algorithm for cryptanalysis currently.Shor’s algorithm can solve the integer factorization problem (IFP) and discrete logarithm problem (DLP) in polynomial-time,which makes the current widely used RSA,ElGamal and ECC public key cryptosystem unsafe any more under the quantum computing environment.Therefore,it is necessary to research the cryptanalysis in the quantum computing environment.Solving the IFP is the core idea of Shor’s algorithm for attacking RSA,but breaking RSA does not have to be solved by solving the IFP.A quantum algorithm is designed to attack the RSA cryptosystem starting from the angle of non-factorization.Focusing on the characteristics of RSA public key cryptosystem,using the quantum Fourier transform,the RSA plaintext $M$ can be got by calculating the ${e^{{th}}}$ root modulus $n$ .That is,without solving the IFP,RSA is broken.Different from the previous practices that cryptanalysts try to recover the private-key,a ciphertext-only attack algorithm for RSA,directly from recovering the plaintext $M$ to start, is presented.Results show that the probability of success of the new algorithm is higher than that of Shor’s algorithm attacking RSA.At the same time,the new algorithm does not recover the RSA plaintext from the ciphertext without factoring the modulus $n$ ,and avoids the restriction that the order of ciphertext $C$ modules $n$ is even.

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We provide a pedagogical presentation of Shor's factoring algorithm, which is a quantum algorithm for factoring very large numbers (of order of hundreds to thousands of bits) in polynomial time. In contrast, all known classical algorithms for the factoring problem take an exponential time to factor such large numbers. Shor's algorithm therefore has profound implication for public-key encryption such as RSA and Diffie–Hellman key exchange. We assume no prior knowledge of Shor's algorithm beyond a basic familiarity with the circuit model of quantum computing. Shor's algorithm contains a number of moving parts, and can be rather daunting at first. The literature is replete with derivations and expositions of Shor's algorithm, but most of them seem to be lacking in essential details, and none of them provide a pedagogical presentation. They require a thicket of appendices and assume a knowledge of quantum algorithms and classical mathematics with which the reader might not be familiar. We therefore start with first principle derivations of the quantum Fourier transform (QFT) and quantum phase estimation (QPE), which are the essential building blocks of Shor's algorithm. We then go on to develop the theory of modular exponentiation (ME) operators, one of the fundamental components of Shor's algorithm, and the place where most of the quantum resources are deployed. We also delve into the number theory that establishes the link between factorization and the period of the modular exponential function. We then apply the QPE algorithm to obtain Shor's factoring algorithm. We also discuss the post-quantum processing and the method of continued fractions, which is used to extract the exact period of the modular exponential function from the approximately measured phase angles of the ME operator. The manuscript then moves on to a series of examples. We first verify the formalism by factoring N=15, the smallest number accessible to Shor's algorithm. We then proceed to factor larger integers, developing a systematic procedure that will find the ME operators for any semi-prime N=p×q (where q and p are prime). Finally, we factor the composite numbers N=21, 33, 35, 143, 247 using the Qiskit simulator. It is observed that the ME operators are somewhat forgiving, and truncated approximate forms are able to extract factors just as well as the exact operators. This is because the method of continued fractions only requires an approximate phase value for its input, which suggests that implementing Shor's algorithm might not be as difficult as first suspected. Quanta 2023; 12: 41–130.

arXiv:2306.09122•Quanta•Sep 15, 2023•8 citations
Shor's algorithm solves the integer factoring and discrete logarithm problems in polynomial time. Therefore, the evaluation of Shor's algorithm is essential for evaluating the security of currently used public-key cryptosystems because the integer factoring and discrete logarithm problems are crucial for the security of these cryptosystems. In this article, a new approximate quantum Fourier transform is proposed, and it is applied to Rines and Chuang's implementation. The proposed implementation requires one-third the number of T gates of the original. Moreover, it requires one-fourth of the T-depth of the original. Finally, a T-scheduling method for running the circuit with the smallest KQ (where K is the number of logical qubits and Q is the circuit depth) is presented.
Shor's algorithm solves the integer factoring and discrete logarithm problems in polynomial time. Therefore, the evaluation of Shor's algorithm is essential for evaluating the security of currently used public-key cryptosystems because the integer factoring and discrete logarithm problems are crucial for the security of these cryptosystems. In this article, a new approximate quantum Fourier transform is proposed, and it is applied to Rines and Chuang's implementation. The proposed implementation requires one-third the number ofTTTgates of the original. Moreover, it requires one-fourth theTTT-depth of the original. Finally, aTTT-scheduling method for running the circuit with the smallest KQ is presented.
Shor’s algorithm is a quantum algorithm that can efficiently solve the problems of integer factorization and discrete logarithms, which potentially break currently used public-key cryptosystems such as RSA and elliptic curve cryptography. However, a significant challenge in solving these problems is the noise inherent in quantum computers. Previous research advanced fault-tolerant techniques such as surface codes to mitigate this noise in quantum computers. Analyzing the security of currently used public-key cryptosystems on fault-tolerant quantum computers is essential. In this paper, we estimate the computational cost required to solve integer factorization using Shor’s algorithm on surface codes. We evaluated computational resources required for surface codes and magic state distillation and derived the computational cost of Shor’s algorithm based on these evaluations. Our computational complexity analysis indicates that there is no significant difference in the order of complexity. However, it underscores the paramount importance of optimizing the coefficient part for future efficiency improvements.
The Shor quantum factorization algorithm allows the factorization or large integers in logarithmic squared time whereas classical algorithms require an exponential time increase with the bit length of the number to be factored. The hardware implementation of the Shor algorithm would thus allow the factorization of the very large integers employed by commercial encryption methods. We propose some modifications of the algorithm by employing some simplification to the stage employing the quantum Fourier transform. The quantum Hadamard transform may be used to replace the quantum Fourier transform in certain cases. This would reduce the hardware complexity of implementation since phase rotation gates with only two states of 0 and π would be required.
This chapter analyzes the applicability of Fourier transformations to determine the periodic structure of finite-length sequences. The classical factorization problem is reformulated to solve it on modern quantum computers with 16 or more qubits. The chapter presents Shor's algorithm for factorization of natural numbers. Performing two basic quantum operations is required to implement the described Shor algorithm, namely exponentiation and quantum discrete Fourier transformation. The chapter estimates the amount of quantum resources needed to solve some asymmetric cryptographic problems using derivatives of the Shor algorithm, with different parameters of these problems, and compares them with the complexity of solving the iterative problem when searching for the key of a symmetric cryptosystem. Using the example of solving the problem of finding the exponent (multiplicative order) of a simple integer modulo by another simple integer, the chapter shows the main features of modeling and engineering implementation of the quantum Shor algorithm.
The emergence of some quantum algorithms has brought a serious threat to modern cryptography,among which Shor’s algorithm is the most important threatening algorithm for cryptanalysis currently.Shor’s algorithm can solve the integer factorization problem (IFP) and discrete logarithm problem (DLP) in polynomial-time,which makes the current widely used RSA,ElGamal and ECC public key cryptosystem unsafe any more under the quantum computing environment.Therefore,it is necessary to research the cryptanalysis in the quantum computing environment.Solving the IFP is the core idea of Shor’s algorithm for attacking RSA,but breaking RSA does not have to be solved by solving the IFP.A quantum algorithm is designed to attack the RSA cryptosystem starting from the angle of non-factorization.Focusing on the characteristics of RSA public key cryptosystem,using the quantum Fourier transform,the RSA plaintext MMM can be got by calculating the eth{e^{{th}}}eth root modulus nnn .That is,without solving the IFP,RSA is broken.Different from the previous practices that cryptanalysts try to recover the private-key,a ciphertext-only attack algorithm for RSA,directly from recovering the plaintext MMM to start, is presented.Results show that the probability of success of the new algorithm is higher than that of Shor’s algorithm attacking RSA.At the same time,the new algorithm does not recover the RSA plaintext from the ciphertext without factoring the modulus nnn ,and avoids the restriction that the order of ciphertext CCC modules nnn is even.
We provide a pedagogical presentation of Shor's factoring algorithm, which is a quantum algorithm for factoring very large numbers (of order of hundreds to thousands of bits) in polynomial time. In contrast, all known classical algorithms for the factoring problem take an exponential time to factor such large numbers. Shor's algorithm therefore has profound implication for public-key encryption such as RSA and Diffie–Hellman key exchange. We assume no prior knowledge of Shor's algorithm beyond a basic familiarity with the circuit model of quantum computing. Shor's algorithm contains a number of moving parts, and can be rather daunting at first. The literature is replete with derivations and expositions of Shor's algorithm, but most of them seem to be lacking in essential details, and none of them provide a pedagogical presentation. They require a thicket of appendices and assume a knowledge of quantum algorithms and classical mathematics with which the reader might not be familiar. We therefore start with first principle derivations of the quantum Fourier transform (QFT) and quantum phase estimation (QPE), which are the essential building blocks of Shor's algorithm. We then go on to develop the theory of modular exponentiation (ME) operators, one of the fundamental components of Shor's algorithm, and the place where most of the quantum resources are deployed. We also delve into the number theory that establishes the link between factorization and the period of the modular exponential function. We then apply the QPE algorithm to obtain Shor's factoring algorithm. We also discuss the post-quantum processing and the method of continued fractions, which is used to extract the exact period of the modular exponential function from the approximately measured phase angles of the ME operator. The manuscript then moves on to a series of examples. We first verify the formalism by factoring N=15, the smallest number accessible to Shor's algorithm. We then proceed to factor larger integers, developing a systematic procedure that will find the ME operators for any semi-prime N=p×q (where q and p are prime). Finally, we factor the composite numbers N=21, 33, 35, 143, 247 using the Qiskit simulator. It is observed that the ME operators are somewhat forgiving, and truncated approximate forms are able to extract factors just as well as the exact operators. This is because the method of continued fractions only requires an approximate phase value for its input, which suggests that implementing Shor's algorithm might not be as difficult as first suspected. Quanta 2023; 12: 41–130.