Quantum Processes and Dynamic Networks in Physical and Biological Systems.

Martin J. Dudziak

Jincheng Zhang

This paper proposes a novel quantum computing architecture inspired by the structure and function of biological neural networks. The core claim is to enhance quantum computing efficiency and fault tolerance by leveraging the inherent properties of biological systems. The mechanism involves modeling quantum bits (qubits) using biologically inspired neuron and synapse models, mimicking their interactions, and utilizing the self-organizing capabilities of neural networks for quantum computation. Unlike traditional quantum computing architectures rooted in classical physics, this approach aims to capitalize on the flexibility and adaptability found within biological systems. The architecture explores concepts such as quantum entanglement and superposition through simulated neural network dynamics, offering a potentially more robust and scalable solution for quantum processing. This work lays the foundation for a biologically-inspired quantum computing paradigm.

José Antonio Fornés

Tadashi Ando, Masanari Asano, Andrei Yu. Khrennikov +2 more

Biological systems have been shown to have quantum-like behaviors by applying the adaptive dynamics view on their interaction networks. In particular, in the process of lactose-glucose metabolism, cells generate probabilistic interference patterns similarly to photons in the two-slit experiment. Such quantum-like interference patterns can be found in biological data, on all scales, from proteins to cognitive, ecological, and social systems. The adaptive dynamics approach covers both biological and physical phenomena, including the ones which are typically associated with quantum physics. We guess that the adaptive dynamics can be used for the clarification of quantum foundations, and the present paper is the first step in this direction. We suggest the use of an algorithm for the numerical simulation of the behavior of a billiard ball-like particle passing through two slits by explicitly considering the influence of the two-slit environment (experimental context). Our simulation successfully mimics the interference pattern obtained experimentally in quantum physics. The interference of photons or electrons by two slits is known as a typical quantum mechanical effect. We do not claim that the adaptive dynamics can reproduce the whole body of quantum mechanics, but we hope that this numerical simulation example will stimulate further extensive studies in this direction-the representation of quantum physical phenomena in an adaptive dynamical framework.

Alexander W. Stern

Dagnell, Michael

This paper develops a conceptual synthesis—bridging physics, biology, and philosophy of mind—based on three axioms that treat consciousness as primary. The relational-fractal ontology proposed here reinterprets quantum measurement, biological evolution, and fundamental forces as coherence dynamics. The framework introduces three axioms: (1) consciousness is primary, (2) consciousness expresses intelligence through network architecture, and (3) mind is the sole property of consciousness. Wavefunction collapse is reinterpreted as the integration of potential quantum states into organic networks capable of sustaining coherence. Post-Darwinian evolution is recast as coherence-seeking dynamics rather than purely random mutation, and the four fundamental forces are interpreted as emergent properties of network interactions. This synthesis situates the proposed framework within contemporary physics, systems theory, and process philosophy.