Quantum optimization with linear Ising penalty functions for customer data science
(2024)
Journal Article
Mirkarimi, P., Shukla, I., Hoyle, D. C., Williams, R., & Chancellor, N. (2024). Quantum optimization with linear Ising penalty functions for customer data science. Physical Review Research, 6(4), Article 043241. https://doi.org/10.1103/physrevresearch.6.043241
Constrained combinatorial optimization problems, which are ubiquitous in industry, can be solved by quantum algorithms such as quantum annealing (QA) and the quantum approximate optimization algorithm (QAOA). In these quantum algorithms, constraints... Read More about Quantum optimization with linear Ising penalty functions for customer data science.