PF2V-WM: Phase-Field Fracture Veil World Models: Fracture as Latent Inference in a Multiscale Anisotropic Medium

Abstract & Diagnostic Summary:This 99-page manuscript documents an intensive diagnostic experimental program investigating continuous-medium phase-field fracture world models (PF2V-WM) for spatial pathing and obstacle selectivity in latent reasoning control. The framework models obstacle constraints as rigid boundaries within an anisotropic multi-scale substrate, simulating trajectory generation as structural fracture propagation. Key Findings & Metrics: Core Metaphor: The architecture treats fuzzy latent pathing probability masses as active stress vectors. It evaluates material-style variations to bypass weak, soft-control baselines by anchoring trajectory paths directly to continuous physical medium equations. The Connectivity Illusion: The diagnostics expose a critical baseline flaw—broad value-field controls can appear fully connected while inadvertently violating and crossing hard obstacle coordinates. Connectivity measurements alone are structurally misleading without strict boundary penalties. Hard Generalization Gains: The phase-field focus model successfully drives a massive structural optimization jump, pushing hard Intersection over Union (IoU) scores from an early material-thin baseline of 0.07–0.12 up into a highly structured 0.19–0.21 range. The Generalization Ceiling: When subjected to a hard generalization layout split featuring severely constrained obstacle distributions, the model retains crisp, selective trajectory activations, reaching a hard IoU of 0.1866. Conclusion:The research establishes that material-style phase-field networks are significantly more obstacle-selective than soft probabilistic alternatives. However, the definitive technical bottleneck is not route awareness, but route hardening—the algorithmic task of forced path crystallization to collapse faint, obstacle-aware latent mass into a thin, continuous, threshold-stable binary corridor. LLM Transparency & Provenance:ChatGPT, Gemini, and Grok assisted with continuous-medium mathematical analogies, LaTeX formatting, and diagnostic visual log analysis under strict validation by the author. Live Google Colab workspace and original conversational verification logs are explicitly detailed on page 1.