English

Near-Optimal Trace Reconstruction for Mildly Separated Strings

Data Structures and Algorithms 2024-12-02 v1

Abstract

In the trace reconstruction problem our goal is to learn an unknown string x{0,1}nx\in \{0,1\}^n given independent traces of xx. A trace is obtained by independently deleting each bit of xx with some probability δ\delta and concatenating the remaining bits. It is a major open question whether the trace reconstruction problem can be solved with a polynomial number of traces when the deletion probability δ\delta is constant. The best known upper bound and lower bounds are respectively exp(O~(n1/5))\exp(\tilde O(n^{1/5})) and Ω~(n3/2)\tilde \Omega(n^{3/2}) both by Chase [Cha21b,Cha21a]. Our main result is that if the string xx is mildly separated, meaning that the number of zeros between any two ones in xx is at least polylognn, and if δ\delta is a sufficiently small constant, then the trace reconstruction problem can be solved with O(nlogn)O(n \log n) traces and in polynomial time.

Keywords

Cite

@article{arxiv.2411.18765,
  title  = {Near-Optimal Trace Reconstruction for Mildly Separated Strings},
  author = {Anders Aamand and Allen Liu and Shyam Narayanan},
  journal= {arXiv preprint arXiv:2411.18765},
  year   = {2024}
}
R2 v1 2026-06-28T20:15:16.343Z