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Yi-Kai Liu
Researcher at National Institute of Standards and Technology
Publications - 65
Citations - 5616
Yi-Kai Liu is an academic researcher from National Institute of Standards and Technology. The author has contributed to research in topics: Quantum algorithm & Quantum tomography. The author has an hindex of 23, co-authored 63 publications receiving 4637 citations. Previous affiliations of Yi-Kai Liu include Lawrence Berkeley National Laboratory & University of California, San Diego.
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Journal ArticleDOI
Quantum state tomography via compressed sensing.
TL;DR: These methods are specialized for quantum states that are fairly pure, and they offer a significant performance improvement on large quantum systems, and are able to reconstruct an unknown density matrix of dimension d and rank r using O(rdlog²d) measurement settings, compared to standard methods that require d² settings.
Journal ArticleDOI
Efficient quantum state tomography
Marcus Cramer,Martin B. Plenio,Steven T. Flammia,Rolando D. Somma,David Gross,Stephen D. Bartlett,Olivier Landon-Cardinal,David Poulin,Yi-Kai Liu +8 more
TL;DR: Two tomography schemes that scale much more favourably than direct tomography with system size are presented, one of them requires unitary operations on a constant number of subsystems, whereas the other requires only local measurements together with more elaborate post-processing.
ReportDOI
Report on Post-Quantum Cryptography
Lidong Chen,Stephen P. Jordan,Yi-Kai Liu,Dustin Moody,René Peralta,Ray A. Perlner,Daniel Smith-Tone +6 more
TL;DR: The National Institute of Standards and Technology (NIST)'s current understanding about the status of quantum computing and post-quantum cryptography is shared, and NIST’s initial plan to move forward is outlined.
Journal ArticleDOI
Direct Fidelity Estimation from Few Pauli Measurements
Steven T. Flammia,Yi-Kai Liu +1 more
TL;DR: A simple method for certifying that an experimental device prepares a desired quantum state ρ, and it provides an estimate of the fidelity between ρ and the actual (arbitrary) state in the lab, up to a constant additive error.
Journal ArticleDOI
Quantum tomography via compressed sensing: error bounds, sample complexity and efficient estimators
TL;DR: In this article, the restricted isometry property of low-rank matrices is used to estimate a low rank density matrix using fewer copies of the state, i.e., the sample complexity of tomography decreases with the rank.