On Boundaries of Evidence — Boundary-State Calculus for Typed Observation, Admissible Transfer, and Falsifiable Persistence

Version 1.3.0 of a foundational preprint proposing Boundary-State Calculus as a typed mathematical audit calculus for claims that move between scientific descriptions. This release adds a fixed-interface operational report envelope, exact component-and-seam localization for finite energy-port residuals, denominator-typed efficiency, and an electromagnetic evidence bridge separating gauge, constitutive, boundary-port, instrument, inverse, coupling, and metrological authority. It retains the version 1.2.0 simulation-evidence framework, ten mathematical fixtures, and two deterministic execution receipts. It does not claim a shared microscopic theory, physical validation, a derivation of the fine-structure constant, a proof of the Riemann Hypothesis, a complete reference implementation, or peer review.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-30
DOI
https://doi.org/10.5281/zenodo.21713285
Primary Topic
Model Reduction and Neural Networks
Type
preprint
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preprint

On Boundaries of Evidence — Boundary-State Calculus for Typed Observation, Admissible Transfer, and Falsifiable Persistence

J. Tree
Zenodo (CERN European Organization for Nuclear Research)
Model Reduction and Neural Networks
preprint

On Boundaries of Evidence — Boundary-State Calculus for Typed Observation, Admissible Transfer, and Falsifiable Persistence

J. Tree
preprint en

Abstract

Version 1.3.0 of a foundational preprint proposing Boundary-State Calculus as a typed mathematical audit calculus for claims that move between scientific descriptions. This release adds a fixed-interface operational report envelope, exact component-and-seam localization for finite energy-port residuals, denominator-typed efficiency, and an electromagnetic evidence bridge separating gauge, constitutive, boundary-port, instrument, inverse, coupling, and metrological authority. It retains the version 1.2.0 simulation-evidence framework, ten mathematical fixtures, and two deterministic execution receipts. It does not claim a shared microscopic theory, physical validation, a derivation of the fine-structure constant, a proof of the Riemann Hypothesis, a complete reference implementation, or peer review.

Zenodo (CERN European Organization for Nuclear Research)
Model Reduction and Neural Networks
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