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. Version 1.1 update:This version strengthens the paper’s operational claim by adding a morphology-space figure that makes the cohort structure visually explicit. In Planck PR3 CMB lensing, Gaussian synthetic controls matched to the same power spectrum remain clearly separated from the observed field in the primary morphology-sensitive diagnostics D1_L2 and Z_mf,, while ΛCDM reconstructions occupy the same morphology regime as the observed data. Version 1.1 also clarifies the robustness framing by stating that the pipeline was subjected to an explicit disconfirmation audit using power-matched Gaussian controls and ΛCDM reconstructions, with the morphology-space separation persisting across these tests. The core contribution remains methodological: standard metric summaries are retained, but extended with a complementary morphology-sensitive layer that improves discrimination between structured cosmological reconstructions and Gaussianized controls. Podcast: https://notebooklm.google.com/notebook/8b5533e5-d7b3-4c33-9bf9-79aaff2ed416?artifactId=59052952-bdca-4383-93f2-393778077f7c