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Related Experiment Video

Updated: Feb 1, 2026

Gradient Echo Quantum Memory in Warm Atomic Vapor

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Published on: November 11, 2013

Quantum Annealing for Prime Factorization.

Shuxian Jiang¹, Keith A Britt², Alexander J McCaskey²

¹Department of Computer Science, Purdue University, West Lafayette, IN, 47906, USA.

Scientific Reports

|December 7, 2018

Summary

This summary is machine-generated.

Researchers developed a resource-efficient framework to solve integer factorization problems using Ising models. This quantum computing approach converts factorization into an executable Ising model, enabling the discovery of prime factors for large composite numbers.

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Area of Science:

Quantum computing
Computational mathematics
Information theory

Background:

Integer factorization is a fundamental problem in cryptography and number theory.
Current factorization methods face scalability challenges with increasing integer size.
Quantum computing offers potential for solving complex computational problems.

Purpose of the Study:

To develop a novel framework for integer factorization using Ising models.
To transform arbitrary integer factorization problems into executable Ising models.
To assess the resource efficiency and scalability of the proposed method.

Main Methods:

Formulating integer factorization as an optimization problem.
Transforming higher-order coupling terms (k ≥ 3) into quadratic terms using ancillary variables.
Utilizing Ising models and quantum annealing (D-Wave 2000Q) for factorization.

Main Results:

Demonstrated factorization of integers 15, 143, 59989, and 376289.
Required 4, 12, 59, and 94 logical qubits, respectively.
Successfully mapped factorization problems to Ising models and found prime factors.

Conclusions:

The developed framework is a general and resource-efficient method for integer factorization.
The approach scales with the number of available qubits, enabling factorization of larger integers.
The method can be combined with other techniques for enhanced performance.