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Neural Network Enhanced Fock State Tomography
P.-H. Wang
,
H.-Y. Hsieh
,
Y.-R. Chen
,
M.-M. Huang
,
J. Ning
,
H.-C. Wu
,
H.-L. Chen
,
Z.-H. Shi
,
O. Steuernagel
,
C.-M. Wu
, …
顯示11作者詳細資料
2025 Conference on Lasers and Electro-Optics, CLEO 2025
2025
DOI:
https://doi.org/10.1364/cleo_fs.2025.ff113_6
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摘要
Diagnosis
Graphic methods
Learning systems
Photonics
Quantum optics
Fock state
Machine-learning
Neural-networks
Parameters estimation
Photon number state
Quantum state tomography
State tomography
Tomography
We present a machine learning enhanced histogram-based quantum state tomography for photon number states and direct parameter estimation on Wigner negativity, offering a diagnostic toolbox for Fock state applications. © 2025 Optica.
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-105021463598&doi=10.1364%2fcleo_fs.2025.ff113_6&partnerID=40&md5=33cb60d349fdc715c4eaf51ef806e186
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題名
Neural Network Enhanced Fock State Tomography
創作者:
P.-H. Wang - National Tsing Hua University
H.-Y. Hsieh - National Tsing Hua University
Y.-R. Chen - National Tsing Hua University
M.-M. Huang
J. Ning - National Tsing Hua University
H.-C. Wu - National Tsing Hua University
H.-L. Chen - National Tsing Hua University
Z.-H. Shi - National Tsing Hua University
O. Steuernagel - National Tsing Hua University
C.-M. Wu - National Tsing Hua University
R.-K. Lee - National Tsing Hua University
出版者
Institute of Electrical and Electronics Engineers Inc.
學術資源類型
會議論文集
出版日期
2025
出版資訊
2025 Conference on Lasers and Electro-Optics, CLEO 2025
語言
英語
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-105021463598&doi=10.1364%2fcleo_fs.2025.ff113_6&partnerID=40&md5=33cb60d349fdc715c4eaf51ef806e186
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