2000 character limit reached
Measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti quantum computer (1811.07594v2)
Published 19 Nov 2018 in quant-ph, cond-mat.mes-hall, cs.AI, cs.ET, and cs.LG
Abstract: We present an experimental realization of a measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti cloud quantum computer. The experiment in this few-qubit superconducting chip faithfully reproduces the theoretical proposal, setting the first steps towards a semiautonomous quantum agent. This experiment paves the way towards quantum reinforcement learning with superconducting circuits.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Collections
Sign up for free to add this paper to one or more collections.