Afterform: Persistent Interference Geometry for History-Dependent Spectral Audio Processing
Afterform is a real-time spectral audio processing architecture in which a decaying complex signal state is separated from a persistent, input-written coupling geometry. Input-derived feature increments update unitary SU(2) links in a rhombic interference network. The signal state may subsequently be cleared while the written geometry remains, allowing a fresh signal to encounter propagation conditions determined by earlier input. The system is evaluated as a write–persist–read memory channel. Across 5,000 randomly sampled pairs of closed histories, SU(2) commutator magnitude strongly predicts fresh-probe distinguishability (Pearson r = 0.770; Spearman ρ = 0.775), establishing a population-level relationship between non-commutativity and readable temporal order. Codebook experiments demonstrate at least 8.8 bits of recoverable information under the tested protocol, with no observed saturation through M = 512. A deliberately strong persistent writable matrix-FDN baseline achieves near-parity in recoverable information, indicating that Afterform's distinction is not raw memory capacity but its architectural organization of memory as local, input-written, confinement-preserving matrix geometry. Further experiments show that the memory is strongly recency-dominated: subsequent writing rapidly overwrites exact recovery of older histories. Across seven source classes, Afterform remains substantially different from a conventional uncoupled resonator bank while remaining much closer to a marginal-matched surrogate. The residual cross-band coherence difference is objectively measurable but small; its perceptual discriminability is therefore left explicitly open for future blinded listener testing. Real-time engineering tests demonstrate block-size-independent operation over 32–1024-sample blocks and practical CPU cost at 44.1, 48 and 96 kHz. The accompanying reproducibility package contains experimental CSV outputs, figures, source material, and C++ harnesses used for objective validation. Version 3.2. DOI: 10.5281/zenodo.22700065.
Authors
- Vasily Psykovsky (ORCID: https://orcid.org/0009-0008-0416-1377)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-11
- DOI
- https://doi.org/10.5281/zenodo.22700065
- Primary Topic
- Speech and Audio Processing
- Type
- preprint