Optimal mean-based algorithms for trace reconstruction

Anindya De, Ryan W. O’Donnell, Rocco A. Servedio · arXiv (Cornell University) · 2016

In the (deletion-channel) trace reconstruction problem, there is an unknown $n$-bit source string $x$. An algorithm is given access to independent traces of $x$, where a trace is formed by deleting each bit of~$x$ independently with probability~$δ$. The goal of the algorithm is to recover~$x$ exactly (with high probability), while minimizing samples (number of traces) and running time. Previously, the best known algorithm for the trace reconstruction problem was due to Holenstein~et~al.; it uses $\exp(\tilde{O}(n^{1/2}))$ samples and running time for any fixed $0 1/2$, the presence of insertions can actually help with trace reconstruction.

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