Linear Response and Effective Screening Operator in the Scalar Temporal Field Ontology

We derive the explicit coefficient structure of the linearized response operator in the Scalar Temporal Field Ontology (STFO). Starting from the scalar field action, we expand around a static matter-core background and obtain expressions for the effective kinetic coefficient and mass term governing perturbations. We show how the operator reduces to a Helmholtz-type form in the weak-gradient regime, establishing the origin of Yukawa-like screening as a controlled approximation. This provides a direct bridge between nonlinear temporal dynamics and the nonlocal screening kernel. This work completes the scalar-sector derivation of the STFO screening framework and supplies the explicit coefficient formulas underlying the reduced second-order screening operator used in subsequent analyses. We derive the explicit coefficient structure of the linearized response operator in the Scalar Temporal Field Ontology (STFO). Starting from the scalar field action, we expand around a static matter-core background and obtain expressions for the effective kinetic coefficient and mass term governing perturbations. We show how the operator reduces to a Helmholtz-type form in the weak-gradient regime, establishing the origin of Yukawa-like screening as a controlled approximation. This provides a direct bridge between nonlinear temporal dynamics and the nonlocal screening kernel. This work completes the scalar-sector derivation of the STFO screening framework and supplies the explicit coefficient formulas underlying the reduced second-order screening operator used in subsequent analyses.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-22
DOI
https://doi.org/10.5281/zenodo.19166138
Primary Topic
Embodied and Extended Cognition
Type
article
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article

Linear Response and Effective Screening Operator in the Scalar Temporal Field Ontology

Cale Scott Howe
Zenodo (CERN European Organization for Nuclear Research)
Embodied and Extended Cognition
article

Linear Response and Effective Screening Operator in the Scalar Temporal Field Ontology

Cale Scott Howe
article en

Abstract

We derive the explicit coefficient structure of the linearized response operator in the Scalar Temporal Field Ontology (STFO). Starting from the scalar field action, we expand around a static matter-core background and obtain expressions for the effective kinetic coefficient and mass term governing perturbations. We show how the operator reduces to a Helmholtz-type form in the weak-gradient regime, establishing the origin of Yukawa-like screening as a controlled approximation. This provides a direct bridge between nonlinear temporal dynamics and the nonlocal screening kernel. This work completes the scalar-sector derivation of the STFO screening framework and supplies the explicit coefficient formulas underlying the reduced second-order screening operator used in subsequent analyses. We derive the explicit coefficient structure of the linearized response operator in the Scalar Temporal Field Ontology (STFO). Starting from the scalar field action, we expand around a static matter-core background and obtain expressions for the effective kinetic coefficient and mass term governing perturbations. We show how the operator reduces to a Helmholtz-type form in the weak-gradient regime, establishing the origin of Yukawa-like screening as a controlled approximation. This provides a direct bridge between nonlinear temporal dynamics and the nonlocal screening kernel. This work completes the scalar-sector derivation of the STFO screening framework and supplies the explicit coefficient formulas underlying the reduced second-order screening operator used in subsequent analyses.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 17%
Embodied and Extended Cognition
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Linear Response and Effective Screening Operator in the Scalar Temporal Field Ontology — Cale Scott Howe · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS