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arXiv · 2610.09998

Probabilistic GC-Constraints for Composite DNA

Humeyra Bodur·Frederik Walter·Antonia Wachter-Zeh
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Abstract

This paper addresses the challenge of encoding biochemical GC-content constraints in composite DNA-based data storage. Previous deterministic models impose high rate penalties by avoiding any possibility for a strand to fall outside the allowed range. To account for the stochastic nature of composite DNA, we introduce an $ε$-probabilistic constraint framework, and derive capacity bounds for global constraints using composition types and for local sliding-window constraints via finite-state Markov chains. Furthermore, we propose a capacity-achieving multi-type enumerative encoder.

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Humeyra Bodur, Frederik Walter, Antonia Wachter-Zeh. 2026-10-07. Probabilistic GC-Constraints for Composite DNA. https://arxiv.org/abs/2610.09998

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