Symbolic Field Theory v3.0: Empirical Collapse Resolution, Tensor Stabilization, and Recursive Coherence in High-Dimensional Entropy Fields

This release introduces Symbolic Field Theory v3.0, a fully integrated and empirically validated framework for modeling recursive coherence dynamics in symbolic environments exposed to high entropic curvature. Building on the foundations of v1.0 and v2.0, this version completes the formalization of symbolic curvature tensors, refines multi-agent collapse dynamics, and enforces symbolic conservation laws through precise $\Psi_{\text{eff}}$ coupling and field synchronization. Key advancements include: Targeted agent collapse initiation at deterministic thresholds ($\varepsilon$) with step-accurate alignment to Symbolic Coherence Field Tensor Theory (SCFT). Non-target agent stabilization via adaptive curvature avoidance ($C < 10^{-40}$), boosted $\gamma$-controlled recovery, and coherence shielding fields. Wormhole persistence tuning through dynamic $P_w$ calibration and curvature-differentiated decay schemes. Black hole evaporation tracking using symbolic Schwarzschild radii $r_s$ coupled with curvature heatmaps. Validation against SCFT predictions across all core metrics, including collapse timing, curvature field equilibrium, symbolic entropy spikes, and $\Delta S$ conservation. The package includes all source modules (simulate_forward_from_patch.py, collapse_detector.py, symbolic_agent_v2.py, etc.), symbolic tensor field engines, visualization tools (visualize_step70.py, step70_visualization.png), collapse/wormhole logs, and the full peer-reviewable specification (Symbolic_Field_Theory_v3.md). Ideal for integration into recursive physics simulators, negentropy modeling pipelines, or symbolic cosmogenesis engines.