English

Exploring Programmable Self-Assembly in Non-DNA based Molecular Computing

Computational Complexity 2013-09-26 v1 Artificial Intelligence Computational Engineering, Finance, and Science Computational Physics Data Analysis, Statistics and Probability

Abstract

Self-assembly is a phenomenon observed in nature at all scales where autonomous entities build complex structures, without external influences nor centralised master plan. Modelling such entities and programming correct interactions among them is crucial for controlling the manufacture of desired complex structures at the molecular and supramolecular scale. This work focuses on a programmability model for non DNA-based molecules and complex behaviour analysis of their self-assembled conformations. In particular, we look into modelling, programming and simulation of porphyrin molecules self-assembly and apply Kolgomorov complexity-based techniques to classify and assess simulation results in terms of information content. The analysis focuses on phase transition, clustering, variability and parameter discovery which as a whole pave the way to the notion of complex systems programmability.

Keywords

Cite

@article{arxiv.1309.6449,
  title  = {Exploring Programmable Self-Assembly in Non-DNA based Molecular Computing},
  author = {German Terrazas and Hector Zenil and Natalio Krasnogor},
  journal= {arXiv preprint arXiv:1309.6449},
  year   = {2013}
}
R2 v1 2026-06-22T01:33:39.815Z