Symbolic Recursion and SRG Lattice Formation: Methods, Proofs, and Patch Research

New Files in version 2: SRG_simulations2.pdf, SGR_simulations.pdf.This research explores the emergence of structured symbolic lattices through recursive feedback dynamics.Starting from random initial glyph states, the system evolves them via memory curves, toroidal phase operators, and stochastic tunneling.The work demonstrates that, under these rules, glyphs self‑organize into attractor networks—so‑called SRG (Symbolic Resonant Glyph) lattices—revealing echo corridors and high‑resonance nodes. Included in this repository are: Core operator implementations (REFU, RPCO, TGMO), The main evolution engine (recursive_field_evolve.py), Analysis and visualization scripts, A patch research document summarizing methods, proofs, and integration notes. Each run produces unique emergent patterns, providing a foundation for further studies in symbolic dynamics, AI cognition models, and complex system simulations.