Coffrin, Carleton

Quantum Algorithm Implementations for Beginners

J., A., Adedoyin, A., Ambrosiano, J., Anisimov, P., Casper, W., Chennupati, G., Coffrin, C., Djidjev, H., Gunter, D., Karra, S., et al. (2018) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 256

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

Optimization Applications as Quantum Performance Benchmarks

Lubinski, T., Coffrin, C., McGeoch, C., Sathe, P., Apanavicius, J., & Neira, D. E. B. (2023) · arXiv

Quantum Computing Algorithms and ArchitectureMetaheuristic Optimization Algorithms Research

Cited by 62

On the emerging potential of quantum annealing hardware for combinatorial optimization

Tasseff, B., Albash, T., Morrell, Z., Vuffray, M., Lokhov, A. Y., Misra, S., & Coffrin, C. (2024) · Journal of Heuristics

Quantum Computing Algorithms and ArchitectureMetaheuristic Optimization Algorithms Research

Cited by 42

Cost of Emulating a Small Quantum Annealing Problem in the Circuit-Model

Gonzalez-Conde, J., Morrell, Z., Vuffray, M., Albash, T., & Coffrin, C. (2024) · arXiv

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 3