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Article Dans Une Revue npj Quantum Information Année : 2021

Variational quantum algorithm with information sharing

Chris N. Self
  • Fonction : Auteur
Kiran E. Khosla
  • Fonction : Auteur
Alistair W. R. Smith
  • Fonction : Auteur
Peter D. Haynes
  • Fonction : Auteur
Johannes Knolle
  • Fonction : Auteur
Florian Mintert
  • Fonction : Auteur
M. S. Kim
  • Fonction : Auteur


We introduce an optimisation method for variational quantum algorithms and experimentally demonstrate a 100-fold improvement in efficiency compared to naive implementations. The effectiveness of our approach is shown by obtaining multi-dimensional energy surfaces for small molecules and a spin model. Our method solves related variational problems in parallel by exploiting the global nature of Bayesian optimisation and sharing information between different optimisers. Parallelisation makes our method ideally suited to the next generation of variational problems with many physical degrees of freedom. This addresses a key challenge in scaling-up quantum algorithms towards demonstrating quantum advantage for problems of real-world interest.



Dates et versions

hal-03612953 , version 1 (18-03-2022)



Chris N. Self, Kiran E. Khosla, Alistair W. R. Smith, Frederic Sauvage, Peter D. Haynes, et al.. Variational quantum algorithm with information sharing. npj Quantum Information, 2021, 7 (1), ⟨10.1038/s41534-021-00452-9⟩. ⟨hal-03612953⟩
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