In this section
@article{Self:2021:10.1038/s41534-021-00452-9,
author = {Self, CN and Khosla, KE and Smith, AWR and Sauvage, F and Haynes, PD and Knolle, J and Mintert, F and Kim, MS},
doi = {10.1038/s41534-021-00452-9},
journal = {npj Quantum Information},
title = {Variational quantum algorithm with information sharing},
url = {http://dx.doi.org/10.1038/s41534-021-00452-9},
volume = {7},
year = {2021}
}
TY - JOUR
AB - 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.
AU - Self,CN
AU - Khosla,KE
AU - Smith,AWR
AU - Sauvage,F
AU - Haynes,PD
AU - Knolle,J
AU - Mintert,F
AU - Kim,MS
DO - 10.1038/s41534-021-00452-9
PY - 2021///
SN - 2056-6387
TI - Variational quantum algorithm with information sharing
T2 - npj Quantum Information
UR - http://dx.doi.org/10.1038/s41534-021-00452-9
UR - http://arxiv.org/abs/2103.16161v1
UR - http://hdl.handle.net/10044/1/90027
VL - 7
ER -