Trace Reconstruction for the Deletion Channel

 

Yuval Peres, Microsoft Research

Joint talk with Microeconomics

Monday, September 11th, 2017
4:00pm 406 Malott


Abstract:

 In the trace reconstruction problem, an unknown string $x$ of $n$ bits is observed through  the deletion channel, which deletes each bit with some constant probability q, yielding a contracted string.  How many independent outputs (traces) of the deletion channel are needed to reconstruct $x$ with high probability?

The best lower bound known is linear in $n$.  Until recently, the best upper bound was exponential in the square root of $n$. We improve the square root to a cube root using statistics of individual output bits and some complex analysis;  this bound is sharp for reconstruction algorithms that only use this statistical information. (Similar results were obtained independently and concurrently by De, O’Donnell and Servedio).  If the string $x$  is random and q<1/2, we can show a subpolynomial number of traces suffices by comparison to a biased random walk.   (Joint works with Fedor Nazarov, STOC 2017 and with Alex Zhai, FOCS 2017).


 

.