Using artificial intelligence to find possibilities while humans gauge their significance is proving to be a powerful new form of scientific discovery.
Back in 2009, computer scientists began experimenting with a simple algorithm that used the process of evolution to discover laws of physics. It worked by crunching the data from simple experiments, such as the swinging motion of a double pendulum. To many people’s surprise, itSince then, physicists and computer scientists have begun to use artificial intelligence techniques to go even further, finding more already known laws, relations and symmetries.
The team began by attempting to automate the design of new quantum optics experiments. These generally consist of a quantum optics bench kitted out with instruments for generating photons, then entangling, reflecting, splitting and detecting them and so on. These attempts had limited success until physicists devised a new way to think about these experiments. Instead of considering a quantum optics experiment as a two-dimensional array of various pieces of equipment, they began to think about each experiment as a graph of the paths of photons and the correlations between them. The process of discovery then becomes a matter of exploring the combinatorial space of different graphs.
They call this novel approach Hyperedge Assembly by Linear Optics or HALO and say that elementary versions of it have already appeared in some quantum information experiments. “[These] can now be understood as special cases of the much more general design principle,” they say.
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