Pelofske, Elijah

Quantum Annealing vs. QAOA: 127 Qubit Higher-Order Ising Problems on NISQ Computers

Pelofske, E., Bärtschi, A., & Eidenbenz, S. (2023) · Lecture Notes in Computer Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 47

Optimizing the Spin Reversal Transform on the D-Wave 2000Q

Pelofske, E., Hahn, G., & Djidjev, H. (2019) · 2019 IEEE International Conference on Rebooting Computing (ICRC)

Quantum Computing Algorithms and ArchitectureMetaheuristic Optimization Algorithms Research

Cited by 26

Provable bounds for noise-free expectation values computed from noisy samples

Barron, S. V., Egger, D. J., Pelofske, E., Bärtschi, A., Eidenbenz, S., Lehmkuehler, M., & Woerner, S. (2024) · Nature Computational Science

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 25

High-Round QAOA for MAX $k$-SAT on Trapped Ion NISQ Devices

Pelofske, E., Bärtschi, A., Golden, J., & Eidenbenz, S. (2023) · 2023 IEEE International Conference on Quantum Computing and Engineering (QCE)

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 15

Noise dynamics of quantum annealers: estimating the effective noise using idle qubits

Pelofske, E., Hahn, G., & Djidjev, H. N. (2023) · Quantum Science and Technology

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 12

Optimizing Embedding-Related Quantum Annealing Parameters for Reducing Hardware Bias

Barbosa, A., Pelofske, E., Hahn, G., & Djidjev, H. N. (2021) · Communications in Computer and Information Science

Quantum Computing Algorithms and ArchitectureMetaheuristic Optimization Algorithms Research

Cited by 2