Error-Control and Digitalization Concepts for Chemical and Biomolecular Information Processing Systems

TL;DR

This paper explores noise control strategies in chemical and biomolecular computing systems, proposing models and methodologies to enhance stability and scalability of information processing networks.

Contribution

It introduces solvable rate-equation models and discusses new concepts for designing noise-resistant chemical and biomolecular gates.

Findings

Models demonstrate effective noise management

Framework supports scalable network design

Outlines future research challenges

Abstract

We consider approaches for controlling the buildup of noise by design of gates for chemical and biomolecular computing, in order to realize stable, scalable networks for multi-step information processing. Solvable rate-equation models are introduced and used to illustrate several recently developed concepts and methodologies. We also outline future challenges and possible research directions.