66 citations to https://www.mathnet.ru/eng/prl4
  1. Hong-Ming Wang, Huan-Yu Ku, Jie-Yien Lin, Hong-Bin Chen, “Deep learning the hierarchy of steering measurement settings of qubit-pair states”, Commun Phys, 7:1 (2024)  crossref
  2. Xin-Yu Chen, Pan Gao, Chu-Dan Qiu, Ya-Nan Lu, Fan Yang, Yuanyuan Zhao, Hang Li, Jiang Zhang, Shijie Wei, Tonghao Xing, Xin-Yu Pan, Dong Ruan, Feihao Zhang, Keren Li, Guilu Long, “A noise-robust quantum dynamics learning protocol based on Choi–Jamiolkowski isomorphism: theory and experiment”, New J. Phys., 26:3 (2024), 033023  crossref
  3. Zi-Jian Xu, Jun-Hong An, “Noise mitigation in quantum teleportation”, Phys. Rev. A, 110:1 (2024)  crossref
  4. Ilya Vilkoviskiy, Dmitry A. Abanin, “Bound on approximating non-Markovian dynamics by tensor networks in the time domain”, Phys. Rev. B, 109:20 (2024)  crossref
  5. Yingwen Wu, Zetong Li, Dafa Zhao, Tian Luan, Xutao Yu, Zaichen Zhang, 2024 5th Information Communication Technologies Conference (ICTC), 2024, 54  crossref
  6. He-Ran Wang, Xiao-Yang Yang, Zhong Wang, “Exact Hidden Markovian Dynamics in Quantum Circuits”, Phys. Rev. Lett., 133:17 (2024)  crossref
  7. Stefano Martina, Stefano Gherardini, Filippo Caruso, “Machine learning classification of non-Markovian noise disturbing quantum dynamics”, Phys. Scr., 98:3 (2023), 035104  crossref
  8. Alexey Melnikov, Mohammad Kordzanganeh, Alexander Alodjants, Ray-Kuang Lee, “Quantum machine learning: from physics to software engineering”, Advances in Physics: X, 8:1 (2023)  crossref
  9. Emilio Onorati, Tamara Kohler, Toby S. Cubitt, “Fitting quantum noise models to tomography data”, Quantum, 7 (2023), 1197  crossref
  10. Hossein T. Dinani, Diego Tancara, Felipe F. Fanchini, Ariel Norambuena, Raul Coto, “Estimating the degree of non-Markovianity using variational quantum circuits”, Quantum Mach. Intell., 5:2 (2023)  crossref
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