Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:1903.00768 · Physical Review A

Experimental study of Shor's factoring algorithm using the IBM Q Experience

Mirko Amico, Zain H. Saleem, Muir Kumph

Published Jul 8, 2019• 75 citations
arXivHTMLPDF

Abstract

We study the results of a compiled version of Shor's factoring algorithm on the ibmqx5 superconducting chip, for the particular case of $N=15$, 21, and 35. The semiclassical quantum Fourier transform is used to implement the algorithm with only a small number of physical qubits, and the circuits are designed to reduce the number of gates to the minimum. We use the square of the statistical overlap to give a quantitative measure of the similarity between the experimentally obtained distribution of phases and the predicted theoretical distribution of phases for different values of the period. This allows us to assign a period to the experimental data without the use of the continued fraction algorithm. A quantitative estimate of the error in our assignment of the period is then given by the overlap coefficient.

DOI
10.1103/physreva.100.012305

Related papers

Shor's Algorithm: Factoring and Cryptanalysis

Bhupendra Singh, Mohankumar Mylsamy, Thamaraimanalan Thangarajan

“Shor's Algorithm: Factoring and Cryptanalysis” focuses on Shor's Algorithm, particularly its application to factoring and cryptanalysis. It begins with an overview of Shor's algorithm, detailing the classical extraction of periods from measured values and the quantum gates required for the Quantum Fourier Transform (QFT). Further, this chapter explores the applications and limitations of Shor's algorithm, including its impact on RSA encryption. A literature review follows, discussing Shor's algorithm in the context of quantum computation, its effectiveness on RSA, and the effects of imperfections on its factorization process. The section also includes an experimental study of Shor's algorithm using IBM Q, followed by a practical implementation of factoring numbers N=21 and N=35. Further, it covers resource estimation, quantum simulations, and different types of simulators in IBM Qiskit, including state vector, QASM, Matrix Product State (MPS), and stabilizer simulators, providing insights into their use cases and the limits of classical simulation.

CRC Press eBooks•Nov 14, 2025•0 citations

Circuit implementation of Shor's algorithm for the factorization of small integers in Qiskit

Iheb Eddine Gharbi, Amor Gueddana, Hichem Eleuch +1 more

To factor an integer N into a product of two other numbers N1 and N2, Shor’s algorithm uses the Quantum Fourier Transform on n qubits, denoted QFTn, to determine the period r of a Modular Exponentiation Function (MEF), which is later used to compute a factor of N. In this work, we present Shor’s algorithm for factoring an integer of n qubits and illustrate an example with n=4. We implement our algorithm using Qiskit and IBM quantum computers, which also can be adapted on other quantum computing platforms with minor adjustments. We discuss the IBM quantum computer limitations for running our circuit and show the impact of device imperfections on the factored result.

Quantum Communications and Quantum Imaging•Aug 13, 2024•2 citations

Implementation of 5-Qubit approach-based Shor's Algorithm in IBM Qiskit

G. R. Mounica, G. Manimaran, Lauret Jerome +1 more

RSA cryptography is a principle part in today's cyber-security frameworks, which intensely depends on the diffi-culty of factorizing large integers. Finding a factor of large prime number is not a small feature compared to the time complexity for computation on a classical computer is far beyond comprehension. Back in 1994, Peter Shor proposed a quantum algorithm to factorize integers much more efficiently than a classical computer. This can effectively break asymmetric cryptosystems such as RSA or Diffie-Hellman, depicted as the most famous quantum algorithm. It leverages the efficacy proclaimed by quantum bits and clearly shows how quantum computers can outperform classical ones in specific tasks. In this paper, we show how Shor's algorithm factorizes an integer into its two prime factors. Shor uses both classical and quantum computation to perform this task in polynomial time, using Euclidean algorithm and find the greatest common divisor (gcd) of two numbers in the classical part. Thereafter, the power of Quantum Fourier Transform (QFT) and Quantum Phase Estimation (QPE) is utilised for period-finding using quantum bits. We have implemented this algorithm on IBM's Quantum Lab and successfully factorized the number 15 into its prime factors as 5 and 3, by using 5 qubits. This paper provides an overview of the implementation of Shor's algorithm involving QPE, QFT, Modular Exponentiation and the corresponding individual implementations, the only prerequisite being, to know how a qubit works.

IEEE Pune Section International Conference (PuneCon)•Dec 16, 2021•17 citations

Demonstration of Shor’s factoring algorithm for N === 21 on IBM quantum processors

Unathi Skosana, Mark Tame

We report a proof-of-concept demonstration of a quantum order-finding algorithm for factoring the integer 21. Our demonstration involves the use of a compiled version of the quantum phase estimation routine, and builds upon a previous demonstration. We go beyond this work by using a configuration of approximate Toffoli gates with residual phase shifts, which preserves the functional correctness and allows us to achieve a complete factoring of [Formula: see text]. We implemented the algorithm on IBM quantum processors using only five qubits and successfully verified the presence of entanglement between the control and work register qubits, which is a necessary condition for the algorithm's speedup in general. The techniques we employ may be useful in carrying out Shor's algorithm for larger integers, or other algorithms in systems with a limited number of noisy qubits.

arXiv:2103.13855•Scientific Reports•Aug 16, 2021•66 citations

From Period Finding to Lattice Sampling: Experimental Insights into Shor's and Regev's Factoring Algorithms

Daniela Falcó, Arturo Rodríguez, Guillermo Rivas +1 more

Quantum algorithms for integer factorization represent one of the most prominent applications of quantum computation, with far-reaching implications for modern cryptography. While Shor's algorithm provides a polynomial-time solution in the ideal quantum model, its practical implementation is severely constrained by the limitations of current noisy intermediate-scale quantum (NISQ) hardware. These constraints have motivated the exploration of alternative factoring algorithms with different structural and resource trade-offs. In this work, we present an experimental study of Regev's quantum factoring algorithm, implemented on real quantum hardware, and compare its behavior with that of Shor's algorithm under analogous conditions. Focusing on the case N = 15, we execute both algorithms on the QMIO quantum computer at the Centro de Supercomputacion de Galicia (CESGA) and contrast the results with one of IBM's open-access quantum computers and ideal simulations. This parallel execution enables a low-level comparison of the two algorithms, highlighting how their respective quantum implementations interact with hardware noise, limited circuit depth, and finite sampling. Our analysis emphasizes the different ways in which Shor's and Regev's algorithms encode arithmetic structure into quantum states through Fourier sampling in one and higher dimensions, respectively, and how these differences manifest in experimental outcomes. Although neither algorithm demonstrates a practical advantage in the small N regime, the results provide insight into their relative robustness and failure modes on contemporary quantum devices. This study illustrates the value of experimental benchmarking of alternative quantum factoring algorithms as a means of understanding the practical implications of algorithmic design choices in the NISQ era.

quant-pharXiv:2606.17647•Jun 17, 2026•0 citations

An integral version of Shor's factoring algorithm

Felix M. Lev

We consider a version of Shor's quantum factoring algorithm such that the quantum Fourier transform is replaced by an extremely simple one where decomposition coefficients take only the values of $1,i,-1,-i$. In numerous calculations which have been carried out so far, our algorithm has been surprisingly stable and never failed. There are numerical indications that the probability of period finding given by the algorithm is a slowly decreasing function of the number to be factorized and is typically less than in Shor's algorithm. On the other hand, quantum computer (QC), capable of implementing our algorithm, will require a much less amount of resources and will be much less error-sensitive than standard QC. We also propose a modification of Coppersmith' Approximate Fast Fourier Transform. The numerical results show that the probability is signifacantly amplified even in the first post integral approximation. Our algorithm can be very useful at early stages of development of quantum computer.

arXiv:quant-ph/0109103•Sep 20, 2001•2 citations
We study the results of a compiled version of Shor's factoring algorithm on the ibmqx5 superconducting chip, for the particular case of N=15N=15N=15, 21, and 35. The semiclassical quantum Fourier transform is used to implement the algorithm with only a small number of physical qubits, and the circuits are designed to reduce the number of gates to the minimum. We use the square of the statistical overlap to give a quantitative measure of the similarity between the experimentally obtained distribution of phases and the predicted theoretical distribution of phases for different values of the period. This allows us to assign a period to the experimental data without the use of the continued fraction algorithm. A quantitative estimate of the error in our assignment of the period is then given by the overlap coefficient.
“Shor's Algorithm: Factoring and Cryptanalysis” focuses on Shor's Algorithm, particularly its application to factoring and cryptanalysis. It begins with an overview of Shor's algorithm, detailing the classical extraction of periods from measured values and the quantum gates required for the Quantum Fourier Transform (QFT). Further, this chapter explores the applications and limitations of Shor's algorithm, including its impact on RSA encryption. A literature review follows, discussing Shor's algorithm in the context of quantum computation, its effectiveness on RSA, and the effects of imperfections on its factorization process. The section also includes an experimental study of Shor's algorithm using IBM Q, followed by a practical implementation of factoring numbers N=21 and N=35. Further, it covers resource estimation, quantum simulations, and different types of simulators in IBM Qiskit, including state vector, QASM, Matrix Product State (MPS), and stabilizer simulators, providing insights into their use cases and the limits of classical simulation.
To factor an integer N into a product of two other numbers N1 and N2, Shor’s algorithm uses the Quantum Fourier Transform on n qubits, denoted QFTn, to determine the period r of a Modular Exponentiation Function (MEF), which is later used to compute a factor of N. In this work, we present Shor’s algorithm for factoring an integer of n qubits and illustrate an example with n=4. We implement our algorithm using Qiskit and IBM quantum computers, which also can be adapted on other quantum computing platforms with minor adjustments. We discuss the IBM quantum computer limitations for running our circuit and show the impact of device imperfections on the factored result.
RSA cryptography is a principle part in today's cyber-security frameworks, which intensely depends on the diffi-culty of factorizing large integers. Finding a factor of large prime number is not a small feature compared to the time complexity for computation on a classical computer is far beyond comprehension. Back in 1994, Peter Shor proposed a quantum algorithm to factorize integers much more efficiently than a classical computer. This can effectively break asymmetric cryptosystems such as RSA or Diffie-Hellman, depicted as the most famous quantum algorithm. It leverages the efficacy proclaimed by quantum bits and clearly shows how quantum computers can outperform classical ones in specific tasks. In this paper, we show how Shor's algorithm factorizes an integer into its two prime factors. Shor uses both classical and quantum computation to perform this task in polynomial time, using Euclidean algorithm and find the greatest common divisor (gcd) of two numbers in the classical part. Thereafter, the power of Quantum Fourier Transform (QFT) and Quantum Phase Estimation (QPE) is utilised for period-finding using quantum bits. We have implemented this algorithm on IBM's Quantum Lab and successfully factorized the number 15 into its prime factors as 5 and 3, by using 5 qubits. This paper provides an overview of the implementation of Shor's algorithm involving QPE, QFT, Modular Exponentiation and the corresponding individual implementations, the only prerequisite being, to know how a qubit works.
We report a proof-of-concept demonstration of a quantum order-finding algorithm for factoring the integer 21. Our demonstration involves the use of a compiled version of the quantum phase estimation routine, and builds upon a previous demonstration. We go beyond this work by using a configuration of approximate Toffoli gates with residual phase shifts, which preserves the functional correctness and allows us to achieve a complete factoring of [Formula: see text]. We implemented the algorithm on IBM quantum processors using only five qubits and successfully verified the presence of entanglement between the control and work register qubits, which is a necessary condition for the algorithm's speedup in general. The techniques we employ may be useful in carrying out Shor's algorithm for larger integers, or other algorithms in systems with a limited number of noisy qubits.
Quantum algorithms for integer factorization represent one of the most prominent applications of quantum computation, with far-reaching implications for modern cryptography. While Shor's algorithm provides a polynomial-time solution in the ideal quantum model, its practical implementation is severely constrained by the limitations of current noisy intermediate-scale quantum (NISQ) hardware. These constraints have motivated the exploration of alternative factoring algorithms with different structural and resource trade-offs. In this work, we present an experimental study of Regev's quantum factoring algorithm, implemented on real quantum hardware, and compare its behavior with that of Shor's algorithm under analogous conditions. Focusing on the case N = 15, we execute both algorithms on the QMIO quantum computer at the Centro de Supercomputacion de Galicia (CESGA) and contrast the results with one of IBM's open-access quantum computers and ideal simulations. This parallel execution enables a low-level comparison of the two algorithms, highlighting how their respective quantum implementations interact with hardware noise, limited circuit depth, and finite sampling. Our analysis emphasizes the different ways in which Shor's and Regev's algorithms encode arithmetic structure into quantum states through Fourier sampling in one and higher dimensions, respectively, and how these differences manifest in experimental outcomes. Although neither algorithm demonstrates a practical advantage in the small N regime, the results provide insight into their relative robustness and failure modes on contemporary quantum devices. This study illustrates the value of experimental benchmarking of alternative quantum factoring algorithms as a means of understanding the practical implications of algorithmic design choices in the NISQ era.
We consider a version of Shor's quantum factoring algorithm such that the quantum Fourier transform is replaced by an extremely simple one where decomposition coefficients take only the values of 1,i,−1,−i1,i,-1,-i1,i,−1,−i. In numerous calculations which have been carried out so far, our algorithm has been surprisingly stable and never failed. There are numerical indications that the probability of period finding given by the algorithm is a slowly decreasing function of the number to be factorized and is typically less than in Shor's algorithm. On the other hand, quantum computer (QC), capable of implementing our algorithm, will require a much less amount of resources and will be much less error-sensitive than standard QC. We also propose a modification of Coppersmith' Approximate Fast Fourier Transform. The numerical results show that the probability is signifacantly amplified even in the first post integral approximation. Our algorithm can be very useful at early stages of development of quantum computer.