{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Melnikov AA"],"funding":["Austrian Science Fund FWF","European Research Council"],"pagination":["1221-1226"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC5819408"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["115(6)"],"pubmed_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"],"journal":["Proceedings of the National Academy of Sciences of the United States of America"],"pubmed_title":["Active learning machine learns to create new quantum experiments."],"pmcid":["PMC5819408"],"funding_grant_id":["SFB FoQuS F4012","W 1259","600645","DK-ALM","SIQS Grant No. 600645 EU-FP7-ICT)","W1259-N27"],"pubmed_authors":["Dunjko V","Tiersch M","Krenn M","Melnikov AA","Zeilinger A","Briegel HJ","Poulsen Nautrup H"],"additional_accession":[]},"is_claimable":false,"name":"Active learning machine learns to create new quantum experiments.","description":"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","dates":{"release":"2018-01-01T00:00:00Z","publication":"2018 Feb","modification":"2025-04-19T07:24:39.135Z","creation":"2019-03-26T23:51:05Z"},"accession":"S-EPMC5819408","cross_references":{"pubmed":["29348200"],"doi":["10.1073/pnas.1714936115"]}}