3 papers
quant-ph2024
Model-aware reinforcement learning for high-performance Bayesian experimental design in quantum metrology
Federico Belliardo, Fabio Zoratti, Florian Marquardt +1
Quantum sensors offer control flexibility during estimation by allowing manipulation by the experimenter across various parameters. For each sensing platform, pinpointing the optim…
quant-ph2024
Application of machine learning to experimental design in quantum mechanics
Federico Belliardo, Fabio Zoratti, Vittorio Giovannetti
The recent advances in machine learning hold great promise for the fields of quantum sensing and metrology. With the help of reinforcement learning, we can tame the complexity of q…
quant-ph2024
Applications of model-aware reinforcement learning in Bayesian quantum metrology
Federico Belliardo, Fabio Zoratti, Vittorio Giovannetti
An important practical problem in the field of quantum metrology and sensors is to find the optimal sequences of controls for the quantum probe that realize optimal adaptive estima…