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Noise-induced transition in optimal solutions of variational quantum algorithms

Journal Article · · TBD
OSTI ID:2323472
Variational quantum algorithms are promising candidates for delivering practical quantum advantage on noisy intermediate-scale quantum (NISQ) hardware. However, optimizing the noisy cost functions associated with these algorithms is challenging for system sizes relevant to quantum advantage. In this work, we investigate the effect of noise on optimization by studying a variational quantum eigensolver (VQE) algorithm calculating the ground state of a spin chain model, and we observe an abrupt transition induced by noise to the optimal solutions. We will present numerical simulations, a demonstration using an IBM quantum processor unit (QPU), and a theoretical analysis indicating the origin of this transition. Our findings suggest that careful analysis is crucial to avoid misinterpreting the noise-induced features as genuine algorithm results.
Research Organization:
Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
DOE Contract Number:
AC02-07CH11359
OSTI ID:
2323472
Report Number(s):
FERMILAB-PUB-24-0103-ETD; arXiv:2403.02762; oai:inspirehep.net:2765160
Journal Information:
TBD, Journal Name: TBD
Country of Publication:
United States
Language:
English

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