Mass ErrorCorrection Codes for PolymerBased Data Storage
Abstract
We consider the problem of correcting mass readout errors in information encoded in binary polymer strings. Our work builds on results for string reconstruction problems using composition multisets [Acharya et al., 2015] and the unique string reconstruction framework proposed in [Pattabiraman et al., 2019]. Binary polymerbased data storage systems [Laure et al., 2016] operate by designing two molecules of significantly different masses to represent the symbols $\{0,1\}$ and perform readouts through noisy tandem mass spectrometry. Tandem mass spectrometers fragment the strings to be read into shorter substrings and only report their masses, often with errors due to imprecise ionization. Modeling the fragmentation process output in terms of composition multisets allows for designing asymptotically optimal codes capable of unique reconstruction and the correction of a single mass error [Pattabiraman et al., 2019] through the use of derivatives of Catalan paths. Nevertheless, no solutions for multiplemass errorcorrections are currently known. Our work addresses this issue by describing the first multipleerror correction codes that use the polynomial factorization approach for the Turnpike problem [Skiena et al., 1990] and the related factorization described in [Acharya et al., 2015]. Adding ReedSolomon type coding redundancy into the corresponding polynomials allows for correcting $t$ mass errors in polynomial time using $t^2\, \log\,k$ redundant bits, where $k$ is the information string length. The redundancy can be improved to $\log\,k + t$. However, no decoding algorithm that runs polynomialtime in both $t$ and $n$ for this scheme are currently known, where $n$ is the length of the coded string.
 Publication:

arXiv eprints
 Pub Date:
 January 2020
 arXiv:
 arXiv:2001.04967
 Bibcode:
 2020arXiv200104967G
 Keywords:

 Computer Science  Information Theory