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Paper Abstract and Keywords
Presentation 2016-11-24 09:30
Reversibility of distance mesures of states with some focus on total variation distance
Keiji Matsumoto (NII)
Abstract (in Japanese) (See Japanese page) 
(in English) Consider a classical memory system, which is in the state described by
probability distribution $p$ or $q$ depending on the value of the bit
recorded. Suppose we embed this information into quantum system, $rho
=Gamma(p)$ or $sigma=Gamma(q)$.

Intuitively, the distribution ${p',q'}$ of measurement outcome on
${rho,sigma}$ should contain strictly less information than ${p,q}$
provided ${rho,sigma}$ is non-commutative. The statement holds if
the information is measured by relative entropy, Renyi relative entropy etc.
However, the assertion is untrue for the total variation distance $Vert
p-qVert_1$: if ${rho,sigma}$ satisfies some not very restrictive
conditions, $Vert p^{prime}-q^{prime}Vert_1$ equals $Vert p-qVert_1%
$. Here we present sufficient condition for general dimension, and necessary
and sufficient condition for qubit.
Keyword (in Japanese) (See Japanese page) 
(in English) $f$-divergence / measurement / optimizatin / information measure / reversibility / / /  
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Conference Information
Committee QIT  
Conference Date 2016-11-24 - 2016-11-25 
Place (in Japanese) (See Japanese page) 
Place (in English) KEK Kobayashi-hall 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Quantum Information 
Paper Information
Registration To QIT 
Conference Code 2016-11-QIT 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Reversibility of distance mesures of states with some focus on total variation distance 
Sub Title (in English)  
Keyword(1) $f$-divergence  
Keyword(2) measurement  
Keyword(3) optimizatin  
Keyword(4) information measure  
Keyword(5) reversibility  
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1st Author's Name Keiji Matsumoto  
1st Author's Affiliation National Institute of Informatics (NII)
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Speaker Author-1 
Date Time 2016-11-24 09:30:00 
Presentation Time 20 minutes 
Registration for QIT 
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