2003
DOI: 10.1103/physreva.68.022308
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Reduction theorems for optimal unambiguous state discrimination of density matrices

Abstract: We present reduction theorems for the problem of optimal unambiguous state discrimination (Optimal USD) of two general density matrices. We show that this problem can be reduced to that of two density matrices that have the same rank n and are described in a Hilbert space of dimensions 2n. We also show how to use the reduction theorems to discriminate unambiguously between N mixed states (N ≥ 2).

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Cited by 76 publications
(89 citation statements)
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“…3) through USD, the measurement scheme becomes less practical involving photon number resolving detectors [29]. The USD of mixed quantum states is a much more subtle issue than that of pure states [30,31,32,33]. Nonetheless, for equal a priori probabilities (which is the FIG.…”
Section: Ultimate Boundsmentioning
confidence: 99%
“…3) through USD, the measurement scheme becomes less practical involving photon number resolving detectors [29]. The USD of mixed quantum states is a much more subtle issue than that of pure states [30,31,32,33]. Nonetheless, for equal a priori probabilities (which is the FIG.…”
Section: Ultimate Boundsmentioning
confidence: 99%
“…In Ref. [23], the authors consider the problem of unambiguous discrimination between two general density matrices.…”
Section: Introductionmentioning
confidence: 99%
“…III, we report the notion of parallel addition that leads to some useful relations for USD in connection with a reduction theorem of Ref. [12]. In Sec.IV, we derive the main result of this paper as a theorem: two necessary and sufficient conditions for the failure probability to reach the bounds are given.…”
Section: Introductionmentioning
confidence: 99%
“…Some special cases have been given for which the corresponding problem can be reduced to USD of pure state case, such as in state filtering [9,10,11] or state comparison [1,11]. The underlying reduction theorems have been stated in [12]. For the general case, necessary and sufficient conditions for the optimality of a POVM were derived in [13,14].…”
Section: Introductionmentioning
confidence: 99%