CMB Evidence for Pre-Metric Physics: Operational Advantage from Extending Metric Physics

This paper reports an operational, morphology-sensitive cohort comparison on Planck PR3 CMB lensing reconstructions. The central empirical result is a strong and persistent separation from Gaussian power-matched controls in the diagnostics D1_L2 and Z_mf, while the observed cohort remains comparatively close to ΛCDM reconstruction controls on the same diagnostics. Using topology-based controls and morphology-sensitive observables, the study identifies a reproducible cohort-separation pattern across tested multipole cutoffs. The claim is intentionally methodological rather than ontological: extending standard metric analysis with a morphology-sensitive (“pre-metric”) observable layer can recover discriminative structure that may remain underutilized in metric-only pipelines. The paper positions this as an operational advantage for analysis design, and as a framework extension compatible with standard metric physics rather than a replacement for it.Listen to a podcast about this paper here: https://notebooklm.google.com/notebook/8b5533e5-d7b3-4c33-9bf9-79aaff2ed416?artifactId=59052952-bdca-4383-93f2-393778077f7c

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-24
DOI
https://doi.org/10.5281/zenodo.18759993
Primary Topic
Cosmology and Gravitation Theories
Type
article
Field-Weighted Citation Impact
0.00
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article

CMB Evidence for Pre-Metric Physics: Operational Advantage from Extending Metric Physics

Marcus van der Erve, GPT-5.2 Thinking
Zenodo (CERN European Organization for Nuclear Research)
Cosmology and Gravitation Theories
article

CMB Evidence for Pre-Metric Physics: Operational Advantage from Extending Metric Physics

Marcus van der Erve, GPT-5.2 Thinking
article en

Abstract

This paper reports an operational, morphology-sensitive cohort comparison on Planck PR3 CMB lensing reconstructions. The central empirical result is a strong and persistent separation from Gaussian power-matched controls in the diagnostics D1_L2 and Z_mf, while the observed cohort remains comparatively close to ΛCDM reconstruction controls on the same diagnostics. Using topology-based controls and morphology-sensitive observables, the study identifies a reproducible cohort-separation pattern across tested multipole cutoffs. The claim is intentionally methodological rather than ontological: extending standard metric analysis with a morphology-sensitive (“pre-metric”) observable layer can recover discriminative structure that may remain underutilized in metric-only pipelines. The paper positions this as an operational advantage for analysis design, and as a framework extension compatible with standard metric physics rather than a replacement for it.Listen to a podcast about this paper here: https://notebooklm.google.com/notebook/8b5533e5-d7b3-4c33-9bf9-79aaff2ed416?artifactId=59052952-bdca-4383-93f2-393778077f7c

Zenodo (CERN European Organization for Nuclear Research)
RPX (United States) (US), OpenAI (United States) (US)
Reduced inequalities
Openalex Percentile: Top 45%
Cosmology and Gravitation Theories
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