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On the experimental feasibility of quantum state reconstruction via
  machine learning
v1v2v3 (latest)

On the experimental feasibility of quantum state reconstruction via machine learning

IEEE Transactions on Quantum Engineering (IEEE Trans. Quantum Eng.), 2020
17 December 2020
Sanjaya Lohani
T. Searles
Brian T. Kirby
R. Glasser
ArXiv (abs)PDFHTML

Papers citing "On the experimental feasibility of quantum state reconstruction via machine learning"

3 / 3 papers shown
Learning Informative Latent Representation for Quantum State Tomography
Learning Informative Latent Representation for Quantum State TomographyIEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), 2023
Hailan Ma
Zhenhong Sun
Daoyi Dong
Dong Gong
383
4
0
08 Jan 2025
Tomography of Quantum States from Structured Measurements via quantum-aware transformer
Tomography of Quantum States from Structured Measurements via quantum-aware transformerIEEE Transactions on Cybernetics (IEEE Trans. Cybern.), 2023
Hailan Ma
Zhenhong Sun
Daoyi Dong
Chunlin Chen
H. Rabitz
473
12
0
09 May 2023
Dimension-adaptive machine-learning-based quantum state reconstruction
Dimension-adaptive machine-learning-based quantum state reconstructionQuantum Machine Intelligence (QMI), 2022
Sanjaya Lohani
Sangita Regmi
J. Lukens
R. Glasser
T. Searles
Brian T. Kirby
235
8
0
11 May 2022
1
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