Advanced Photonics, Volume. 5, Issue 1, 016005(2023)
Deep reinforcement learning for quantum multiparameter estimation
[12] A. Shlosberg et al. Adaptive estimation of quantum observables(2021).
[13] G. E. Box, G. C. Tiao. Bayesian Inference in Statistical Analysis(2011).
[14] C. W. Helstrom. Quantum Detection and Estimation Theory(1976).
[17] M. Valeri et al. Experimental multiparameter quantum metrology in adaptive regime(2022).
[24] G. Carleo et al. Machine learning and the physical sciences. Rev. Mod. Phys., 91, 045002(2019).
[26] V. Gebhart et al. Learning quantum systems(2022).
[27] A. Dawid et al. Modern applications of machine learning in quantum sciences(2022).
[41] E. Alpaydin. Introduction to Machine Learning(2020).
[42] R. S. Sutton, A. G. Barto. Reinforcement Learning: An Introduction(2018).
[63] R. Osellame, G. Cerullo, R. Ramponi. Femtosecond Laser Micromachining: Photonic and Microfluidic Devices in Transparent Materials, 123(2012).
[65] M. G. Paris. Quantum estimation for quantum technology. Int. J. Quantum Inf., 7, 125-137(2009).
[72] D. P. Kingma, J. Ba. Adam: a method for stochastic optimization(2014).
Get Citation
Copy Citation Text
Valeria Cimini, Mauro Valeri, Emanuele Polino, Simone Piacentini, Francesco Ceccarelli, Giacomo Corrielli, Nicolò Spagnolo, Roberto Osellame, Fabio Sciarrino, "Deep reinforcement learning for quantum multiparameter estimation," Adv. Photon. 5, 016005 (2023)
Category: Research Articles
Received: Sep. 27, 2022
Accepted: Dec. 27, 2022
Posted: Jan. 4, 2023
Published Online: Feb. 7, 2023
The Author Email: Sciarrino Fabio (fabio.sciarrino@uniroma1.it)