Topological, Quantum, and Molecular Information Approaches to Computation and Intelligence

Dear Colleagues,

This Topic explores the interplay between topological, quantum, and molecular information structures, and their roles in shaping intelligent computation across both artificial and biological systems. We welcome pioneering theoretical and experimental contributions that draw upon topological quantum computing, braid groups, modular tensor categories, and molecular regulatory mechanisms—including those based on DNA, RNA, and miRNA—to propose novel frameworks for learning, inference, decision-making, and biologically inspired computation.

We also encourage submissions that investigate fundamental physical or algebraic architectures of cognition and natural intelligence, especially those grounded in quantum symmetries, non-Abelian computation, and topological robustness.

The goal is to foster collaboration across quantum physics, mathematics, artificial intelligence, molecular biology, and information theory, with an emphasis on frameworks that integrate logic, structure, and evolution into new paradigms of computation.

Topics (non‑exhaustive)

• Anyon-based topological quantum computing (e.g., SU(2)_k, Fibonacci anyons)
• Modular tensor categories and braid group representations in computation
• Quantum neural networks and variational quantum learning
• Quantum-inspired AI: cognition, decision theory, and hybrid architectures
• SL(2,C) symmetries and topological operations in learning models
• Algebraic and topological modeling of DNA, RNA, and miRNA dynamics
• Quantum and classical logic in gene regulation and molecular computation
• Category-theoretic modeling of biological information networks
• Quantum/molecular models of consciousness (e.g., with microtubules, anyon cognition)
• Topological invariants and non-locality in cognitive architectures

Dr. Michel Planat
Prof. Dr. Edward A. Rietman
Topic Editors