Computational physics2026Theory paper

Training Collapse as Parametric Resonance: A Floquet–Mathieu Reframe

A theoretical reframe casting a subset of deep-network training instabilities as parametric resonance under the Mathieu equation, with Floquet monodromy spectra as computable stability boundaries. The work is an open research program with falsifiable predictions, not a closed result. No live filing.

PROGRAMThe Escapement
CURRENT POSTUREOpen publication candidate
DISCLOSUREPublic briefing
01 / PUBLIC ABSTRACT

ORIENTATION, NOT OVERCLAIM.

A theoretical reframe casting a subset of deep-network training instabilities as parametric resonance under the Mathieu equation, with Floquet monodromy spectra as computable stability boundaries. The work is an open research program with falsifiable predictions, not a closed result. No live filing.

02 / CURRENT POSTURE

The public surface contains an orientation briefing. The full manuscript and supporting package remain subject to revision and release control.

03 / EVIDENCE BOUNDARY

This page does not imply peer review, acceptance, experimental replication, or public availability of every supporting asset. The canonical register distinguishes those states explicitly.

04 / RELEASE GATE

Authorship, source verification, claims-to-evidence mapping, reproducibility, and patent-disclosure review must be cleared before any final external release.

PUBLIC APERTURE

PUBLIC BRIEFING

The public surface contains an orientation briefing. The full manuscript and supporting package remain subject to revision and release control.

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