Ternary Logic Fold [432Hz]: A Reproducible Dataset for Ternary Symbolic Dynamics, Dwell-Time Quantization, and Null-Model Testing

This dataset accompanies the paper “Ternary Logic Fold [432Hz]: A Multi-Scale Signal Analysis of Ternary-State Dynamics and Quantized Dwell Times” and contains the primary audio artifact, derived signal stems, analysis figures, a reproducibility notebook, and a comparative supplemental report. The core analysis treats the audio not as a musical object but as a dynamical system. A low-frequency carrier (20–80 Hz) is isolated and mapped to a ternary symbolic alphabet (−1, 0, +1) using amplitude-based thresholds. The resulting symbolic sequence exhibits constrained transition topology (no direct −1↔+1 transitions), strongly quantized dwell times at millisecond scale, and evidence of higher-order temporal structure. To evaluate claims of second-order recurrence structure, the dataset includes a null-model analysis comparing the observed ternary sequence against (i) a shuffle baseline preserving symbol frequencies and (ii) a constrained first-order Markov baseline preserving transition probabilities. The observed recurrence accuracy (0.489) exceeds both shuffle and first-order Markov null models (means 0.361 and 0.465, respectively; p ≈ 0.005), indicating statistically significant second-order temporal structure not explained by lower-order dynamics. All results are reproducible using the included Jupyter notebook, which executes deterministically given the provided audio files and standard scientific Python libraries. A supplemental third-party analysis (Google Gemini) is included for comparison and is explicitly bounded in the accompanying paper to distinguish verified measurements from speculative interpretations.