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A Graph-Based Classical and Quantum Approach to Deterministic L-System Inference

Quantum Physics 2025-07-02 v3 Computation and Language Data Structures and Algorithms Formal Languages and Automata Theory Machine Learning

Abstract

L-systems can be made to model and create simulations of many biological processes, such as plant development. Finding an L-system for a given process is typically solved by hand, by experts, in a massively time-consuming process. It would be significant if this could be done automatically from data, such as from sequences of images. In this paper, we are interested in inferring a particular type of L-system, deterministic context-free L-system (D0L-system) from a sequence of strings. We introduce the characteristic graph of a sequence of strings, which we then utilize to translate our problem (inferring D0L-systems) in polynomial time into the maximum independent set problem (MIS) and the SAT problem. After that, we offer a classical exact algorithm and an approximate quantum algorithm for the problem.

Keywords

Cite

@article{arxiv.2411.19906,
  title  = {A Graph-Based Classical and Quantum Approach to Deterministic L-System Inference},
  author = {Ali Lotfi and Ian McQuillan and Steven Rayan},
  journal= {arXiv preprint arXiv:2411.19906},
  year   = {2025}
}

Comments

17 pages, 1 figure

R2 v1 2026-06-28T20:17:11.603Z