2015
DOI: 10.1103/physreva.91.032123
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Majorization approach to entropic uncertainty relations for coarse-grained observables

Abstract: We improve the entropic uncertainty relations for position and momentum coarse-grained measurements. We derive the continuous, coarse-grained counterparts of the discrete uncertainty relations based on the concept of majorization. The obtained entropic inequalities involve two Rényi entropies of the same order, and thus go beyond the standard scenario with conjugated parameters. In a special case describing the sum of two Shannon entropies the majorization-based bounds significantly outperform the currently kn… Show more

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Cited by 62 publications
(73 citation statements)
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References 54 publications
(107 reference statements)
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“…The joint uncertainty measures considered here are of the form p q  r r Å ( ( ) ( )). A nontrivial u v , ( ) for this restricted class can be found using the methods in [25,26].…”
Section: Universal Uncertainty Relationsmentioning
confidence: 99%
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“…The joint uncertainty measures considered here are of the form p q  r r Å ( ( ) ( )). A nontrivial u v , ( ) for this restricted class can be found using the methods in [25,26].…”
Section: Universal Uncertainty Relationsmentioning
confidence: 99%
“…Pioneered by Hirschman [4], many works [11][12][13][14][15][16][17][18] 2 have used entropies to quantify uncertainty, culminating in a recent surge of quantum information-theoretic treatments of the uncertainty principle [19][20][21][22][23][24][25][26][27][28][29][30]. An important contribution of these recent works is the formulation of uncertainty relations applicable on a quantum system correlated with a quantum memory; such relations are used to strengthen the security proofs of cryptographic tasks [31,32].…”
Section: Introductionmentioning
confidence: 99%
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“…Questions of their optimality are addressed in [14]. Other approaches are based on the sum of variances [15,16] and on majorization relations [17][18][19][20][21]. The variance-based formulation was recently applied to noise and disturbance [22].…”
Section: Introductionmentioning
confidence: 99%