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Approximate Trace Reconstruction from a Single Trace

Xi Chen, Anindya De, Chin Ho Lee, Rocco A. Servedio, Sandip Sinha

2023Year
2Citations
1Top-tier citations

Abstract

The well-known trace reconstruction problem is the problem of inferring an unknown source string x ∈ 0, 1 n from independent "traces", i.e. copies of x that have been corrupted by a δ-deletion channel which independently deletes each bit of x with probability δ and concatenates the surviving bits. The current paper considers the extreme data-limited regime in which only a single trace is provided to the reconstruction algorithm. In this setting exact reconstruction is of course impossible, and the question is to what accuracy the source string x can be approximately reconstructed.

We give a detailed study of this question, providing algorithms and lower bounds for the high, intermediate, and low deletion rate regimes in both the worst-case (x is arbitrary) and average-case (x is drawn uniformly from 0, 1 n ) models. In several cases the lower bounds we establish are matched by computationally efficient algorithms that we provide.

We highlight our results for the high deletion rate regime: roughly speaking, they show that

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