Quantum algorithms for numerical differentiation of expected values with respect to parameters-Reference-Cited by-同舟云学术

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Quantum algorithms for numerical differentiation of expected values with respect to parameters

Published:2022-03 Issue:3 Volume:21 Page:
ISSN:1570-0755
Container-title:Quantum Information Processing
language:en
Short-container-title:Quantum Inf Process

Author:

Miyamoto Koichi^ORCID

Funder

Ministry of Education, Culture, Sports, Science and Technology

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Modeling and Simulation,Signal Processing,Theoretical Computer Science,Statistical and Nonlinear Physics,Electronic, Optical and Magnetic Materials

Link

https://link.springer.com/content/pdf/10.1007/s11128-022-03453-5.pdf

Reference58 articles.

1. Montanaro, A.: Quantum speedup of Monte Carlo methods. Proc. R. Soc. Ser. A 471(2181), 20150301 (2015)

2. Suzuki, Y., et al.: Amplitude estimation without phase estimation. Quantum Inf. Process. 19, 75 (2020)

3. Herbert, S.: Quantum Monte-Carlo Integration: the full advantage in minimal circuit depth. arXiv:2105.09100 (2021)

4. Brassard, G., et al.: Quantum amplitude amplification and estimation. Contemp. Math. 305, 53 (2002)

5. Aaronson, S., Rall, P.: Quantum approximate counting, simplified. In Proceedings of Symposium on Simplicity in Algorithms, pp. 24–32. SIAM (2020)

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