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  4. Benchmarking the Variational Quantum Eigensolver using different quantum hardware
 
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2023
Conference Paper
Title

Benchmarking the Variational Quantum Eigensolver using different quantum hardware

Abstract
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.
Author(s)
Bentellis, Amine
Fraunhofer-Institut für Kognitive Systeme IKS  
Matic-Flierl, Andrea
Fraunhofer-Institut für Kognitive Systeme IKS  
Mendl, Christian B.
Technische Universität München  
Lorenz, Jeanette Miriam  orcid-logo
Fraunhofer-Institut für Kognitive Systeme IKS  
Mainwork
IEEE Quantum Week 2023. Proceedings. Vol.III: Second IEEE Quantum Science and Engineering Education Conference, QSEEC 2023  
Conference
International Conference on Quantum Computing and Engineering 2023  
Quantum Week 2023  
Quantum Science and Engineering Education Conference 2023  
Open Access
File(s)
Download (303.77 KB)
Rights
Use according to copyright law
DOI
10.1109/QCE57702.2023.00065
10.24406/h-457796
Additional full text version
Landing Page
Language
English
Fraunhofer-Institut für Kognitive Systeme IKS  
Fraunhofer Group
Fraunhofer-Verbund IUK-Technologie  
Keyword(s)
  • quantum computing

  • Variational Quantum Eigensolver

  • VQE

  • quantum hardware comparison

  • ion trap quantum computer

  • superconduction quantum computer

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