Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > CLEO_FS > 2023 > FM3A > FM3A.4

Benchmarking Machine Learning-Derived W State Witnesses on NISQ Hardware

Alexander C. B. Greenwood, Eric Y. Zhu, Larry T. H. Wu, Brian T. Kirby, and Li Qian

Not Accessible

Your library or personal account may give you access

Abstract

We find that our W state witnesses derived with a Support Vector Machine have comparable noise tolerance while requiring fewer measurements than the fidelity method; this result is physically verified on an IBM Quantum Processor.

© 2023 The Author(s)

PDF Article
More Like This
Machine Learning Derived Entanglement Witnesses

Larry T.H. Wu, Eric Y. Zhu, and Li Qian
FW3N.1 CLEO: QELS_Fundamental Science (CLEO:FS) 2021

Benchmarking a Quantum Random Number Generator with Machine Learning

Jing Yan Haw, Nhan Duy Truong, Hong Jie Ng, Raymond Ho, Syed Assad, Chao Wang, Ping Koy Lam, and Omid Kavehei
W3B.5 Quantum Information and Measurement (QIM) 2021

Bayesian quantum state reconstruction with a learning-based tuned prior

Sangita Regmi, Ashley N. Blackwell, Amirali Khannejad, Sanjaya Lohani, Joseph M. Lukens, Ryan T. Glasser, Brian T. Kirby, and Thomas A. Searles
QM4B.3 Quantum 2.0 (QUANTUM) 2023

View More...
Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use