ArticleScientific reports2019
Quantum annealing for systems of polynomial equations.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Novel real number representations in Ising machines and performance evaluation: Combinatorial random number sum and constant division.PloS one · 2024Article
- Exploring the Limitations of Hybrid Adiabatic Quantum Computing for Emission Tomography Reconstruction.Journal of imaging · 2023Article
- Controlled precision QUBO-based algorithm to compute eigenvectors of symmetric matrices.PloS one · 2022Article
- Adiabatic quantum linear regression.Scientific reports · 2021Article
- QUBO formulations for training machine learning models.Scientific reports · 2021Article
- Parallel in time dynamics with quantum annealers.Scientific reports · 2020Article
- Hybrid classical-quantum linear solver using Noisy Intermediate-Scale Quantum machines.Scientific reports · 2019Article
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Authors and funding
4 authors.
Funding
Abstract
Numerous scientific and engineering applications require numerically solving systems of equations. Classically solving a general set of polynomial equations requires iterative solvers, while linear equations may be solved either by direct matrix inversion or iteratively with judicious preconditioning. However, the convergence of iterative algorithms is highly variable and depends, in part, on the condition number. We present a direct method for solving general systems of polynomial equations based on quantum annealing, and we validate this method using a system of second-order polynomial equations solved on a commercially available quantum annealer. We then demonstrate applications for linear regression, and discuss in more detail the scaling behavior for general systems of linear equations with respect to problem size, condition number, and search precision. Finally, we define an iterative annealing process and demonstrate its efficacy in solving a linear system to a tolerance of 10
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Registered trials
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