Conditional Neutrino Interfaces and Posterior Mixtures in the Axis Model
Andrew Morton · Public preprint · Conditional neutrino mathematics
Derives propagation bounds and statistical mixture identities for explicitly supplied neutrino-interface models.
Current program context
The current revision withdraws the earlier environmental mass mechanism and the interpretation of posterior bimodality as evidence for two physical branches. Historical fits remain descriptive provenance.
Abstract
This correction separates common-body component typing, conditional propagation, statistical identities, and historical posterior fitting in the Axis Model. The classical body and weak-component interfaces are imported from their originating authorities. For a supplied finite-dimensional Hermitian effective operator, we state a propagation bound that retains time ordering. We distinguish one dataset-global latent branch from independent event-level branches and derive the normalized posterior-mixture identity for the former. Explicit counterexamples show that two components need not produce two modes and that coincident branches need not produce a unimodal posterior. Earlier two-Gaussian fits to published neutrino posteriors are retained as descriptive computational provenance, without refitting or interpreting them as experiment-level likelihood validation. A versioned derivative checks only these mathematical statements and artifact provenance. Physical neutrino population, kinetic support, masses, environmental response, and branch selection remain originating inputs.
Scope
The mathematical statements use declared operators and latent-variable models. Physical neutrino masses, kinetic support, environmental response and branch selection require additional originating inputs.
Paper and supporting files
The Zenodo record includes the current source and reproducibility archives. The historical posterior dataset is a separate imported-data record.
Read the current paper and supporting files on Zenodo
Historical neutrino posterior data
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Abstract checked 28 August 2026 · public release 27 August 2026.