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Free keywords:
Quantum Physics, quant-ph
Abstract:
Despite rapid progress in the field, it is still challenging to discover new
ways to take advantage of quantum computation: all quantum algorithms need to
be designed by hand, and quantum mechanics is notoriously counterintuitive. In
this paper, we study how artificial intelligence, in the form of program
synthesis, may help to overcome some of these difficulties, by showing how a
computer can incrementally learn concepts relevant for quantum circuit
synthesis with experience, and reuse them in unseen tasks. In particular, we
focus on the decomposition of unitary matrices into quantum circuits, and we
show how, starting from a set of elementary gates, we can automatically
discover a library of new useful composite gates and use them to decompose more
and more complicated unitaries.
