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IEEE Access

An Evaluation of Computational Complexity of Shor’s Algorithm on Surface Codes for Factorization

Kento Oonishi, Noboru Kunihiro

Published Jan 1, 2026• 2 citations
Publisher

Abstract

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.

DOI
10.1109/access.2026.3665887

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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.
The complexity of public key algorithms like RSA and variants of Elgamal is based on the involvement of exponentiation in encryption and decryption. RSA is based on integer factorization and variants of Elgamal or based on discrete logarithms and are formed as hard problems. To achieve the perceived level of security, the required key length for public key cryptosystem needs to be determined. Quantum computers are capable of conducting an exponential number of simultaneous computations because of which they can find factors in polynomial time. Shor’s algorithm is popular algorithm for factoring huge integers in polynomial time on quantum computers. This paper presents RSA algorithm followed by various possible attacks for factoring and demonstrates Shor’s algorithm for factoring and discuss results for interpretations.
The ongoing development of Quantum Computing (QC) is a breakthrough paradigm that holds the power to revolutionize the way we process information and solve complex problems today. Quantum Computation works on the fundamental principles of Superposition and Entanglement, enabling Quantum Computers to Leverage the power of Physics in Computing. QC has the potential to revolutionize fields such as Drug Development, Financial Modeling, Optimization, and Cryptography. Shor’s algorithm, a quantum algorithm used to factorize large numbers, poses significant threats to RSA, a widely used public key cryptosystem. RSA relies on the difficulty of factoring large semi-primes to keep its security. Shor's algorithm's ability to factorize quickly on a quantum computer undermines RSA's security assumptions, necessitating the exploration of post-quantum cryptographic solutions to ensure secure communication in the quantum era. The goal of this paper is to assess the present state of Shor's algorithm implementation and efficiency, specifically its application in the context of compromising public key cryptosystems like RSA.
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.
The ongoing development of Quantum Computing (QC) is a breakthrough paradigm that holds the power to revolutionize the way we process information and solve complex problems today. Quantum Computation works on the fundamental principles of Superposition and Entanglement, enabling Quantum Computers to Leverage the power of Physics in Computing. QC has the potential to revolutionize fields such as Drug Development, Financial Modeling, Optimization, and Cryptography. Shor’s algorithm, a quantum algorithm used to factorize large numbers, poses significant threats to RSA, a widely used public key cryptosystem. RSA relies on the difficulty of factoring large semi-primes to keep its security. Shor's algorithm's ability to factorize quickly on a quantum computer undermines RSA's security assumptions, necessitating the exploration of post-quantum cryptographic solutions to ensure secure communication in the quantum era. The goal of this paper is to assess the present state of Shor's algorithm implementation and efficiency, specifically its application in the context of compromising public key cryptosystems like RSA.
Quantum computers pose a fundamental threat to widely deployed public-key cryptosystems, such as RSA and ECC, by enabling efficient integer factorization using Shor's algorithm. Theoretical resource estimates suggest that 2048-bit RSA keys could be broken using Shor's algorithm with fewer than a million noisy qubits. Although such machines do not yet exist, the availability of smaller, cloud-accessible quantum processors and open-source implementations of Shor's algorithm raises the question of what key sizes can realistically be factored with today's platforms. In this work, we experimentally investigate Shor's algorithm on several cloud-based quantum computers using publicly available implementations. Our results reveal a substantial gap between the capabilities of current quantum hardware and the requirements for factoring cryptographically relevant integers. In particular, we observe that circuit constructions still need to be highly specific for each modulus, and that machine fidelities are unstable, with high and fluctuating error rates.
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.