2018
DOI: 10.1088/1751-8121/aac87c
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Extremal distributions under approximate majorization

Abstract: Although an input distribution may not majorize a target distribution, it may majorize a distribution which is close to the target. Here we consider a notion of approximate majorization. For any distribution, and given a distance δ, we find the approximate distributions which majorize (are majorized by) all other distributions within the distance δ. We call these the steepest and flattest approximation. This enables one to compute how close one can get to a given target distribution under a process governed by… Show more

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Cited by 22 publications
(38 citation statements)
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“…In addition, we showed that the notion of approximate majorization is in strong connection with the property of completeness of the majorization lattice [20,42]. Indeed, the flattest and steepest approximations are nothing more than the infimum and supremum of the corresponding set, respectively, and they can be calculated only from their vertices.…”
Section: Discussionmentioning
confidence: 91%
See 2 more Smart Citations
“…In addition, we showed that the notion of approximate majorization is in strong connection with the property of completeness of the majorization lattice [20,42]. Indeed, the flattest and steepest approximations are nothing more than the infimum and supremum of the corresponding set, respectively, and they can be calculated only from their vertices.…”
Section: Discussionmentioning
confidence: 91%
“…, of x 0 given in [20,42] , although the algorithms to obtain them are different to the ones presented here. Thus, we see that the notion of approximate majorization is in strong connection with the property of completeness of the majorization lattice.…”
Section: Infimum and Supremum Over Convex Polytopesmentioning
confidence: 95%
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“…This characterization is not useful enough to obtain the supremum and infimum, since one needs to know a priori the vertices of B p (x). Notwithstanding, for p = 1, it has recently been shown not only how to compute supremum and infimum, but also that they are the maximum and minimum of the ball B 1 (x) [18,31]. Here, we complete the order-theoretic characterization of the balls by analyzing the case p = ∞, showing that B ∞ (x) also admits extremal probability vectors.…”
Section: Order-theoretic Properties Ofmentioning
confidence: 86%
“…This majorization-based UR provides universal applicability to any appropriate uncertainty functions with such an uncertainty-order preserving property. Besides uncertainty relations, the concept of majorization is applied to various topics, such as quantum thermodynamics [31] and coherence [32].…”
Section: Introductionmentioning
confidence: 99%