Counting, Computing, and Pattern Recognition with Self-Assembling Non-Reciprocal DNA Tiles

TL;DR

This paper demonstrates that self-assembling DNA tile systems with programmable non-reciprocal interactions can perform computational tasks like counting, pattern recognition, and modulo calculations, integrating sensing and actuation in a physical platform.

Contribution

It introduces design principles for non-equilibrium DNA tile assemblies capable of complex computation and pattern recognition, advancing physical computation in matter.

Findings

Assemblies can perform counting and modulo computations.

Systems recognize specific input patterns.

Energy-efficient non-reciprocal interactions enable dynamic transitions.

Abstract

Harnessing the intrinsic dynamics of physical systems for information processing opens new avenues for computation embodied in matter. Using simulations of a model system, we show that assemblies of DNA tiles capable of self-organizing into multiple target structures can perform basic computational tasks analogous to those of finite-state automata when equipped with programmable non-reciprocal interactions that drive controlled dynamical transitions between these structures. By establishing design rules for multifarious self-assembly while budgeting the energy input required to drive these non-equilibrium transitions, we demonstrate that these systems can execute a wide variety of tasks including counting, computing modulo functions, and recognizing specific input patterns. This framework integrates memory, sensing, and actuation within a single physical platform, paving the way toward energy-efficient physical computation embedded in materials ranging from DNA and enzymes to proteins and colloids.