Bootstrapping quantum process tomography via a perturbative ansatz.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
27 Feb 2020
27 Feb 2020
Historique:
received:
26
06
2019
accepted:
06
02
2020
entrez:
29
2
2020
pubmed:
29
2
2020
medline:
29
2
2020
Statut:
epublish
Résumé
Quantum process tomography has become increasingly critical as the need grows for robust verification and validation of candidate quantum processors, since it plays a key role in both performance assessment and debugging. However, as these processors grow in size, standard process tomography becomes an almost impossible task. Here, we present an approach for efficient quantum process tomography that uses a physically motivated ansatz for an unknown quantum process. Our ansatz bootstraps to an effective description for an unknown process on a multi-qubit processor from pairwise two-qubit tomographic data. Further, our approach can inherit insensitivity to system preparation and measurement error from the two-qubit tomography scheme. We benchmark our approach using numerical simulation of noisy three-qubit gates, and show that it produces highly accurate characterizations of quantum processes. Further, we demonstrate our approach experimentally on a superconducting quantum processor, building three-qubit gate reconstructions from two-qubit tomographic data.
Identifiants
pubmed: 32107382
doi: 10.1038/s41467-020-14873-1
pii: 10.1038/s41467-020-14873-1
pmc: PMC7046656
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1084Références
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