UFT-ID 2.0: Audio-Based Qutrit-State Analysis and Emergent Dynamics Report

This dataset contains the full analytical report and figure set for a sonic test of UFT-ID 2.0, evaluating how a generated audio signal (Qutrit Cycle.wav) exhibits structural, dynamical, and informational patterns predicted by the Unified Field Theory of Information Dynamics. Using spectral, statistical, and machine-learning–based analysis tools, the study extracts four key diagnostics: Spectrogram (Log-Frequency Substrate Mapping)Demonstrates a persistent global-wave backbone with layered local excitations, matching the dual-layer ontology of UFT-ID 2.0. Qutrit-State Segmentation TimelineClusters RMS and spectral-centroid microstates into the ternary logical modes |F⟩ (Collapse), |T⟩ (Stability), and |U⟩ (Emergence), revealing clear cycling behavior. Self-Similarity Matrix (Lineage Preservation Test)Identifies recurring excitation families and motif reconstruction across time—an audio analogue of meaning-preserving correction dynamics. Meaning-Current Modulation AnalysisShows partial coupling between onset activity and spectral tension (corr ≈ 0.30), consistent with the back-reaction mechanism encoded in the UFT-ID action functional. The PDF included in this dataset contains the complete analysis, figure captions, and structural results.This dataset serves as a multimodal demonstration of UFT-ID 2.0 applied to generative audio and provides a reproducible model for testing informational dynamics in sonic systems.