Machine learning for optical quantum metrology

Machine learning (ML) is one of the most acclaimed areas of science and technology, leading to countless real-world benefits, from industry to healthcare. ML involves creating algorithms to perform specific tasks by recognizing patterns in the data and without requiring exten-sive instructions, namely without being explicitly programmed. This possibility has recently attracted the attention of a broad community of scientists interested in learning, controlling, and making optimal use of quantum systems of increasing complexity,1,2 potentially leading to revolutionary progresses in many fields.