Numerical Examination of LRAE Symmetron Parameters Against Atomic Clock and Solar System Constraints

This work presents a numerical investigation of the Local Relative Acceleration Expansion (LRAE) with Symmetron-type density-dependent screening. Static boundary value problems and dynamic relaxation runs demonstrate that the model is consistent with current atomic clock and Solar-System constraints. In Version 1.3, we add systematic parameter scans across $(\mu,\lambda)$, yielding contour maps of relative clock drifts and maximum allowed coupling strengths. The results confirm that realistic couplings predict drifts far below present detection thresholds. Full scan data are provided as supplementary CSV files. Authorship: Andreas Jung In collaboration with: ChatGPT (OpenAI) Lizenz: Creative Commons Attribution Non Commercial No Derivatives 4.0 International (CC BY-NC-ND 4.0) Published: July 2025Kontakt: [email protected]

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-17
DOI
https://doi.org/10.5281/zenodo.16889773
Primary Topic
Theoretical and Computational Physics
Type
article
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article

Numerical Examination of LRAE Symmetron Parameters Against Atomic Clock and Solar System Constraints

Zenodo (CERN European Organization for Nuclear Research)
Theoretical and Computational Physics
article

Numerical Examination of LRAE Symmetron Parameters Against Atomic Clock and Solar System Constraints

article en

Abstract

This work presents a numerical investigation of the Local Relative Acceleration Expansion (LRAE) with Symmetron-type density-dependent screening. Static boundary value problems and dynamic relaxation runs demonstrate that the model is consistent with current atomic clock and Solar-System constraints. In Version 1.3, we add systematic parameter scans across $(\mu,\lambda)$, yielding contour maps of relative clock drifts and maximum allowed coupling strengths. The results confirm that realistic couplings predict drifts far below present detection thresholds. Full scan data are provided as supplementary CSV files. Authorship: Andreas Jung In collaboration with: ChatGPT (OpenAI) Lizenz: Creative Commons Attribution Non Commercial No Derivatives 4.0 International (CC BY-NC-ND 4.0) Published: July 2025Kontakt: [email protected]

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 60%
Theoretical and Computational Physics
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