Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published November 1, 2006 | public
Journal Article Open

Optimal and efficient decoding of concatenated quantum block codes

Poulin, David

Abstract

We consider the problem of optimally decoding a quantum error correction code—that is, to find the optimal recovery procedure given the outcomes of partial "check" measurements on the system. In general, this problem is NP hard. However, we demonstrate that for concatenated block codes, the optimal decoding can be efficiently computed using a message-passing algorithm. We compare the performance of the message-passing algorithm to that of the widespread blockwise hard decoding technique. Our Monte Carlo results using the five-qubit and Steane's code on a depolarizing channel demonstrate significant advantages of the message-passing algorithms in two respects: (i) Optimal decoding increases by as much as 94% the error threshold below which the error correction procedure can be used to reliably send information over a noisy channel; and (ii) for noise levels below these thresholds, the probability of error after optimal decoding is suppressed at a significantly higher rate, leading to a substantial reduction of the error correction overhead.

Additional Information

©2006 The American Physical Society (Received 23 June 2006; published 22 November 2006) I thank Harold Ollivier for several useful conversations on message-passing algorithms and quantum error correction, and Graeme Smith and Jon Yard for comments. This work was supported, in part, by the Gordon and Betty Moore Foundation through Caltech's Center for the Physics of Information, by the National Science Foundation under Grant No. PHY-0456720, and by the National Science and Engineering Research Council of Canada.

Files

POUpra06.pdf
Files (147.9 kB)
Name Size Download all
md5:a26073eb6bef61d0c88db729a5009f28
147.9 kB Preview Download

Additional details

Created:
August 22, 2023
Modified:
October 16, 2023