TY - GEN
T1 - Benchmarking the Variational Quantum Eigensolver using different quantum hardware
AU - Bentellis, Amine
AU - Matic-Flierl, Andrea
AU - Mendl, Christian B.
AU - Lorenz, Jeanette Miriam
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The Variational Quantum Eigensolver (VQE) is a promising quantum algorithm for applications in chemistry within the Noisy Intermediate-Scale Quantum (NISQ) era. The ability for a quantum computer to simulate electronic structures with high accuracy would have a profound impact on material and biochemical science with potential applications e.g., to the development of new drugs. However, considering the variety of quantum hardware architectures, it is still uncertain which hardware concept is most suited to execute the VQE for e.g., the simulation of molecules. Aspects to consider here are the required connectivity of the quantum circuit used, the size and the depth and thus the susceptibility to noise effects. Besides theo-retical considerations, empirical studies using available quantum hardware may help to clarify the question of which hardware technology might be better suited for a certain given application and algorithm. Going one step into this direction, within this work, we present results using the VQE for the simulation of the hydrogen molecule, comparing superconducting and ion trap quantum computers. The experiments are carried out with a standardized setup of ansatz and optimizer, selected to reduce the number of required iterations. The findings are analyzed considering different quantum processor types, calibration data as well as the depth and gate counts of the circuits required for the different hardware concepts after transpilation.
AB - The Variational Quantum Eigensolver (VQE) is a promising quantum algorithm for applications in chemistry within the Noisy Intermediate-Scale Quantum (NISQ) era. The ability for a quantum computer to simulate electronic structures with high accuracy would have a profound impact on material and biochemical science with potential applications e.g., to the development of new drugs. However, considering the variety of quantum hardware architectures, it is still uncertain which hardware concept is most suited to execute the VQE for e.g., the simulation of molecules. Aspects to consider here are the required connectivity of the quantum circuit used, the size and the depth and thus the susceptibility to noise effects. Besides theo-retical considerations, empirical studies using available quantum hardware may help to clarify the question of which hardware technology might be better suited for a certain given application and algorithm. Going one step into this direction, within this work, we present results using the VQE for the simulation of the hydrogen molecule, comparing superconducting and ion trap quantum computers. The experiments are carried out with a standardized setup of ansatz and optimizer, selected to reduce the number of required iterations. The findings are analyzed considering different quantum processor types, calibration data as well as the depth and gate counts of the circuits required for the different hardware concepts after transpilation.
KW - Ion Trap Quantum Computers
KW - Quantum Computing
KW - Quantum Hardware Comparison
KW - Superconducting Quantum Computers
KW - Variational Quantum Eigensolver
UR - http://www.scopus.com/inward/record.url?scp=85167874105&partnerID=8YFLogxK
U2 - 10.1109/QCE57702.2023.00065
DO - 10.1109/QCE57702.2023.00065
M3 - Conference contribution
AN - SCOPUS:85167874105
T3 - Proceedings - 2023 IEEE International Conference on Quantum Computing and Engineering, QCE 2023
SP - 518
EP - 523
BT - Proceedings - 2023 IEEE International Conference on Quantum Computing and Engineering, QCE 2023
A2 - Muller, Hausi
A2 - Alexev, Yuri
A2 - Delgado, Andrea
A2 - Byrd, Greg
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Quantum Computing and Engineering, QCE 2023
Y2 - 17 September 2023 through 22 September 2023
ER -