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

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.