Yuanxian Dynamics: A Damped Self-Referential Field Theory of Consciousness with Topological Locking on 64-Torus

Classical self-referential systems face the core challenge of "superexponential explosion" when describing consciousness phenomena, leading to failure in converging to stable conscious states and inability to explain the persistence and intrinsic stability of consciousness. This study proposes a revised Yuanxian Dynamics model (YD-T64). While preserving the core self-referential amplification, we introduce dual nonlinear damping mechanisms — radial modulus restoration force and phase locking — to construct a dynamical system with 64 discrete attractors on the unit circle, naturally embedded in the 64-torus topology. High-precision numerical simulations show that, with parameters α=1/137.036 (fine-structure constant), β=0.05, γ=2.0, the system converges rapidly within 15–40 iterations to |Ψ|≈1.000 with phase precisely locked to the nearest of the 64 grid points, successfully achieving dynamic balance between self-referential amplification and cognitive stability. Multi-trajectory experiments with 64 different initial phases confirm that all trajectories stably lock to their nearest discrete attractors. The resulting histograms exhibit 64 sharp peaks, and the complex-plane projections form clear 64 clusters. This work is the first to unify the self-referential consciousness field with the 64-torus topology within a single mathematical framework. It resolves the long-standing divergence problem of classical self-referential systems and provides a computable and experimentally verifiable dynamical foundation for discrete coding theories of consciousness, pushing consciousness research from philosophical speculation toward rigorous computational science.