Machine Learning-Enhanced Quantum State Tomography with Direct Parameter Estimations
Instead of using the reconstruction model in training a truncated density matrix, we develop a high-performance, lightweight, and easy-to-install supervised characteristic model by generating the target parameters directly. © 2023 The Author(s)
Authors
- Chien-Ming Wu (ORCID: https://orcid.org/0000-0003-3191-8845)
- Popo Yang (ORCID: https://orcid.org/0000-0002-2469-6220)
- Ray‐Kuang Lee (ORCID: https://orcid.org/0000-0002-7171-7274)
- Ole Steuernagel (ORCID: https://orcid.org/0000-0001-6089-7022)
- Hsien-Yi Hsieh (ORCID: https://orcid.org/0000-0001-5227-8248)
- Hua Li Chen
- Po-Han Wang
- Zi-Hao Shi
- Hsun-Chung Wu
- Yi-Ru Chen
- Jingyu Ning
Institutions
- National Tsing Hua University (TW)
Publication Details
- Published
- 2024-08-04
- DOI
- https://doi.org/10.1109/cleo-pr60912.2024.10676693
- Primary Topic
- Quantum Computing Algorithms and Architecture
- Type
- article
- Field-Weighted Citation Impact
- 0.00