Yarkoni, Sheir

Quantum annealing for industry applications: introduction and review

Yarkoni, S., Raponi, E., Bäck, T., & Schmitt, S. (2022) · Reports on Progress in Physics

Quantum Computing Algorithms and ArchitectureMetaheuristic Optimization Algorithms Research

Cited by 341

Challenges and opportunities in quantum optimization

Abbas, A., Ambainis, A., Augustino, B., Bärtschi, A., Buhrman, H., Coffrin, C., Cortiana, G., Dunjko, V., Egger, D. J., Elmegreen, B. G., et al. (2024) · Nature Reviews Physics

Quantum Computing Algorithms and ArchitectureMetaheuristic Optimization Algorithms Research

Cited by 201

Benchmarking a quantum annealing processor with the time-to-target metric

King, J., Yarkoni, S., Nevisi, M. M., Hilton, J. P., & McGeoch, C. C. (2015) · arXiv

Quantum Computing Algorithms and ArchitectureParallel Computing and Optimization Techniques

Cited by 77

Quantum Shuttle: traffic navigation with Quantum computing

Yarkoni, S., Neukart, F., Tagle, E. M. G., Magiera, N., Mehta, B., Hire, K., Narkhede, S., & Hofmann, M. (2020) · Proceedings of the 1st ACM SIGSOFT International Workshop on Architectures and Paradigms for Engineering Quantum Software

Quantum Computing Algorithms and ArchitectureTransportation Planning and Optimization

Cited by 50

Beating classical heuristics for the binary paint shop problem with the quantum approximate optimization algorithm

Streif, M., Yarkoni, S., Skolik, A., Neukart, F., & Leib, M. (2021) · Physical Review A

Quantum Computing Algorithms and ArchitectureComplexity and Algorithms in Graphs

Cited by 41