Active learning machine learns to create new quantum experiments.

ABSTRACT: How useful can machine learning be in a quantum laboratory? Here we raise the question of the potential of intelligent machines in the context of scientific research. A major motivation for the present work is the unknown reachability of various entanglement classes in quantum experiments. We investigate this question by using the projective simulation model, a physics-oriented approach to artificial intelligence. In our approach, the projective simulation system is challenged to design complex photonic quantum experiments that produce high-dimensional entangled multiphoton states, which are of high interest in modern quantum experiments. The artificial intelligence system learns to create a variety of entangled states and improves the efficiency of their realization. In the process, the s

SUBMITTER: Melnikov AA 

PROVIDER: S-EPMC5819408 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature