Albash, Tameem

Adiabatic quantum computation

Albash, T., & Lidar, D. A. (2018) · Reviews of Modern Physics

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,546

Demonstration of a Scaling Advantage for a Quantum Annealer over Simulated Annealing

Albash, T., & Lidar, D. A. (2018) · Physical Review X

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 238

Reexamining classical and quantum models for the D-Wave One processor: The role of excited states and ground state degeneracy

Albash, T., Rønnow, T. F., Troyer, M., & Lidar, D. A. (2015) · The European Physical Journal Special Topics

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 96

Nested quantum annealing correction

Vinci, W., Albash, T., & Lidar, D. A. (2016) · npj Quantum Information

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 57

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