1. Conditional uncertainty principle
- Author
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Andrzej Grudka, Waldemar Kłobus, Michał Horodecki, Justyna Łodyga, Gilad Gour, Varun Narasimhachar, and School of Physical and Mathematical Sciences
- Subjects
Quantum Physics ,Uncertainty principle ,Mathematical relation ,01 natural sciences ,Upper and lower bounds ,010305 fluids & plasmas ,Monotone polygon ,Physics [Science] ,Conditional quantum entropy ,0103 physical sciences ,Operational framework ,Applied mathematics ,Entropic uncertainty ,Conditional Majorization ,010306 general physics ,Majorization ,Algorithm ,Mathematics - Abstract
We develop a general operational framework that formalizes the concept of conditional uncertainty in a measure-independent fashion. Our formalism is built upon a mathematical relation which we call conditional majorization. We define conditional majorization and, for the case of classical memory, we provide its thorough characterization in terms of monotones, i.e., functions that preserve the partial order under conditional majorization. We demonstrate the application of this framework by deriving two types of memory-assisted uncertainty relations, (1) a monotone-based conditional uncertainty relation and (2) a universal measure-independent conditional uncertainty relation, both of which set a lower bound on the minimal uncertainty that Bob has about Alice's pair of incompatible measurements, conditioned on arbitrary measurement that Bob makes on his own system. We next compare the obtained relations with their existing entropic counterparts and find that they are at least independent. Ministry of Education (MOE) National Research Foundation (NRF) Published version This work is supported by ERC Advanced Grant QOLAPS and National Science Centre Grants Mae- stro No. DEC-2011/02/A/ST2/00305 and OPUS 9 No. 2015/17/B/ST2/01945. V.N. acknowledges financial support from the Ministry of Education of Singapore, the National Research Foundation (NRF Fellowship Reference No. NRF- NRFF2016-02), and the John Templeton Foundation (Grant No. 54914).
- Published
- 2018