{"paper":{"title":"Programmable quantum state discriminators with simple programs","arxiv_id":"quant-ph/0602164","primary_cat":"quant-ph","submitted_at":"2006-02-20T17:03:19+00:00","version_compiled":"v1"},"notice":"Every quoted sentence is the authors' text from the arXiv listing abstract. Labels and probabilities are the outputs of classifier-1.13.0 on the question bank abstract-p1-20260923, exactly as returned. No sentence in this record was written by a language model.","schema":"pith.compiled-record/v0","status":"compiled","abstract":{"source":"arXiv listing abstract v1","sentences":[{"i":0,"p":0.97,"id":"s0","own":true,"role":"contribution","text":"We describe a class of programmable devices that can discriminate between two quantum states. We consider two cases.","hedge":{"p":0.94,"label":"asserted"},"own_p":0.84,"main_claim_p":0.03,"quantitative":false,"quantitative_p":0.27,"role_probabilities":{"gap":0.0,"method":0.0,"result":0.0,"background":0.03,"limitation":0.0,"future_work":0.0,"contribution":0.97,"interpretation":0.0}},{"i":1,"p":0.45,"id":"s1","own":false,"role":"method","text":"In the first, both states are unknown.","hedge":{"p":0.89,"label":"asserted"},"own_p":0.21,"main_claim_p":0.02,"quantitative":false,"quantitative_p":0.16,"role_probabilities":{"gap":0.0,"method":0.45,"result":0.0,"background":0.31,"limitation":0.0,"future_work":0.0,"contribution":0.24,"interpretation":0.0}},{"i":2,"p":0.95,"id":"s2","own":false,"role":"method","text":"One copy of each of the unknown states is provided as input, or program, for the two program registers, and the data state, which is guaranteed to be prepared in one of the program states, is fed into the data register of the device.","hedge":{"p":0.97,"label":"asserted"},"own_p":0.43,"main_claim_p":0.04,"quantitative":true,"quantitative_p":0.78,"role_probabilities":{"gap":0.0,"method":0.95,"result":0.0,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.05,"interpretation":0.0}},{"i":3,"p":0.57,"id":"s3","own":true,"role":"method","text":"This device will then tell us, in an optimal way, which of the templates stored in the program registers the data state matches.","hedge":{"p":0.99,"label":"asserted"},"own_p":0.55,"main_claim_p":0.08,"quantitative":false,"quantitative_p":0.06,"role_probabilities":{"gap":0.0,"method":0.57,"result":0.26,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.16,"interpretation":0.01}},{"i":4,"p":0.4,"id":"s4","own":false,"role":"contribution","text":"In the second case, we know one of the states while the other is unknown.","hedge":{"p":0.97,"label":"asserted"},"own_p":0.32,"main_claim_p":0.02,"quantitative":false,"quantitative_p":0.2,"role_probabilities":{"gap":0.0,"method":0.34,"result":0.0,"background":0.26,"limitation":0.0,"future_work":0.0,"contribution":0.4,"interpretation":0.0}},{"i":5,"p":0.96,"id":"s5","own":true,"role":"method","text":"One copy of the unknown state is fed into the single program register, and the data state which is guaranteed to be prepared in either the program state or the known state, is fed into the data register.","hedge":{"p":0.97,"label":"asserted"},"own_p":0.5,"main_claim_p":0.04,"quantitative":true,"quantitative_p":0.65,"role_probabilities":{"gap":0.0,"method":0.96,"result":0.0,"background":0.01,"limitation":0.0,"future_work":0.0,"contribution":0.03,"interpretation":0.0}},{"i":6,"p":0.68,"id":"s6","own":true,"role":"method","text":"The device will then tell us, again optimally, whether the data state matches the template or is the known state.","hedge":{"p":1.0,"label":"asserted"},"own_p":0.75,"main_claim_p":0.07,"quantitative":false,"quantitative_p":0.06,"role_probabilities":{"gap":0.0,"method":0.68,"result":0.14,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.18,"interpretation":0.0}},{"i":7,"p":0.91,"id":"s7","own":true,"role":"contribution","text":"We determine two types of optimal devices.","hedge":{"p":0.99,"label":"asserted"},"own_p":0.91,"main_claim_p":0.05,"quantitative":false,"quantitative_p":0.38,"role_probabilities":{"gap":0.0,"method":0.08,"result":0.01,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.91,"interpretation":0.0}},{"i":8,"p":0.77,"id":"s8","own":true,"role":"contribution","text":"The first performs discrimination with minimum error, the second performs optimal unambiguous discrimination.","hedge":{"p":1.0,"label":"asserted"},"own_p":0.9,"main_claim_p":0.09,"quantitative":false,"quantitative_p":0.2,"role_probabilities":{"gap":0.0,"method":0.19,"result":0.04,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.77,"interpretation":0.0}},{"i":9,"p":0.97,"id":"s9","own":true,"role":"method","text":"In all cases we first treat the simpler problem of only one copy of the data state and then generalize the treatment to n copies.","hedge":{"p":0.98,"label":"asserted"},"own_p":0.9,"main_claim_p":0.09,"quantitative":true,"quantitative_p":0.5,"role_probabilities":{"gap":0.0,"method":0.97,"result":0.0,"background":0.0,"limitation":0.0,"future_work":0.0,"contribution":0.03,"interpretation":0.0}},{"i":10,"p":0.99,"id":"s10","own":true,"role":"result","text":"In comparison to other works we find that providing n > 1 copies of the data state yields higher success probabilities than providing n > 1 copies of the program 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