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  4. Error Exponents and Strong Converse Exponents for Classical Data Compression with Quantum Side Information
 
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Error Exponents and Strong Converse Exponents for Classical Data Compression with Quantum Side Information

Journal
IEEE International Symposium on Information Theory - Proceedings
Journal Volume
2018-June
Pages
2162-2166
Date Issued
2018
Author(s)
Cheng H.-C
Hanson E.P
Datta N
Hsieh M.-H.
HAO-CHUNG CHENG  
DOI
10.1109/ISIT.2018.8437348
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85052434027&doi=10.1109%2fISIT.2018.8437348&partnerID=40&md5=889e6d768e21e66f2fede891f4b6e664
https://scholars.lib.ntu.edu.tw/handle/123456789/580527
Abstract
In this paper, we analyze classical data compression with quantum side information (also known as the classical-quantum Slepian- Wolf protocol) in the so-called large and moderate deviation regimes. In the non-asymptotic setting, the protocol involves compressing classical sequences of finite length n and decoding them with the assistance of quantum side information. In the large deviation regime, the compression rate is fixed, and we obtain bounds on the error exponent function, which characterizes the minimal probability of error as a function of the rate. Devetak and Winter showed that the asymptotic data compression limit for this protocol is given by a conditional entropy. For any protocol with a rate below this quantity, the probability of error converges to one asymptotically and its speed of convergence is given by the strong converse exponent function. We obtain finite blocklength bounds on this function, and determine exactly its asymptotic value, thus improving on previous results by Tomamichel. In the moderate deviation regime for the compression rate, the latter is no longer considered to be fixed. It is allowed to depend on the blocklength n, but assumed to decay slowly to the asymptotic data compression limit. Starting from a rate above this limit, we determine the speed of convergence of the error probability to zero and show that it is given in terms of the conditional information variance. Our results complement earlier results obtained by Tomamichel and Hayashi, in which they analyzed the so-called small deviation regime of this protocol. ? 2018 IEEE.
Type
conference paper

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