2022
DOI: 10.22331/q-2022-02-21-658
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Online identification of symmetric pure states

Abstract: We consider online strategies for discriminating between symmetric pure states with zero error when n copies of the states are provided. Optimized online strategies involve local, possibly adaptive measurements on each copy and are optimal at each step, which makes them robust in front of particle losses or an abrupt termination of the discrimination process. We first review previous results on binary minimum and zero error discrimination with local measurements that achieve the maximum success probability set… Show more

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Cited by 4 publications
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“…The objective is that the verifier passes the test with a worst-case probability of δ. They consider independent sequential measurements [11].…”
Section: Introductionmentioning
confidence: 99%
“…The objective is that the verifier passes the test with a worst-case probability of δ. They consider independent sequential measurements [11].…”
Section: Introductionmentioning
confidence: 99%