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researcher

H. Yuen

52 papers hereh-index 221.4k citations51 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author1
  • middle author2
  • last author44

Across the 50 of 52 papers where every author was matched, so the position is known.

fields
  • quant-ph43
  • cs.CC4
  • cs.AI1
  • cs.CR1
  • cs.IT1
  • hep-th1
same name
  • H. Yuen — 51 papers, h 30
  • H. Yuen — 5 papers, h 7
  • H. Yuen — 1 paper, h 5
  • H. Yuen — 1 paper, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20102026
most citedExploring entanglement and optimization within the Hamiltonian Variational Ansatz

235 citations · 405 across the 36 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

quant-ph2022

Pseudorandom (Function-Like) Quantum State Generators: New Definitions and Applications

Prabhanjan Ananth, Aditya Gulati, Luowen Qian +1

Pseudorandom quantum states (PRS) are efficiently constructible states that are computationally indistinguishable from being Haar-random, and have recently found cryptographic appl…

quant-ph2022

Unitary property testing lower bounds by polynomials

Adrian She, Henry Yuen

We study unitary property testing, where a quantum algorithm is given query access to a black-box unitary and has to decide whether it satisfies some property. In addition to conta…

quant-ph2022

Testing and Learning Quantum Juntas Nearly Optimally

Thomas Chen, Shivam Nadimpalli, Henry Yuen

We consider the problem of testing and learning quantum k-juntas: n-qubit unitary matrices which act non-trivially on just k of the n qubits and as the identity on the rest…

quant-ph2022★ 26 cited

An Improved Sample Complexity Lower Bound for (Fidelity) Quantum State Tomography

Henry Yuen

We show that Ω(rd/ε) copies of an unknown rank-r, dimension-d quantum mixed state are necessary in order to learn a classical description with 1−ε fidelity. This improves…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.