NT30: COCM Route 3 Analysis Pipeline — Complete Python Implementation

Complete Python implementation of the COCM Route 3 analysis pipeline for measuring I = P(2k_COCM)/P(k_COCM) and e_I = (I/1910)^(1/4.86) (NT25), testing Claim 7 (e > 0) and the NT25 unification condition e_PA = e_J = e_I. The pipeline implements: (1) COCMPhysics class with all corpus constants and relations (k_COCM = 0.003 Mpc^-1, I_0 = 1910, alpha = 4.86, three routes to e, NT25 unification check); (2) comoving coordinate conversion (flat LCDM); (3) survey mask generation respecting eROSITA-DE and eROSITA-RU galactic footprints; (4) Landy-Szalay xi(r) estimator with spherical Hankel transform to P(k); (5) bootstrap and jackknife spatial error estimation; (6) Claim 7 status and NT25 unification check. Primary tracer: eROSITA-DE DR1 cluster catalogue (erass1cl_main_v3.2.fits, NT28). Validation tracer: eROSITA-RU TDEs (NT29). API infrastructure adapted from external scripts (Perplexity AI and anonymous AI, May 2026); physical methodology from the COCM corpus.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-30
DOI
https://doi.org/10.5281/zenodo.20464646
Primary Topic
Computational Physics and Python Applications
Type
preprint
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preprint

NT30: COCM Route 3 Analysis Pipeline — Complete Python Implementation

José Luis Vázquez González
Zenodo (CERN European Organization for Nuclear Research)
Computational Physics and Python Applications
preprint

NT30: COCM Route 3 Analysis Pipeline — Complete Python Implementation

José Luis Vázquez González
preprint en

Abstract

Complete Python implementation of the COCM Route 3 analysis pipeline for measuring I = P(2k_COCM)/P(k_COCM) and e_I = (I/1910)^(1/4.86) (NT25), testing Claim 7 (e > 0) and the NT25 unification condition e_PA = e_J = e_I. The pipeline implements: (1) COCMPhysics class with all corpus constants and relations (k_COCM = 0.003 Mpc^-1, I_0 = 1910, alpha = 4.86, three routes to e, NT25 unification check); (2) comoving coordinate conversion (flat LCDM); (3) survey mask generation respecting eROSITA-DE and eROSITA-RU galactic footprints; (4) Landy-Szalay xi(r) estimator with spherical Hankel transform to P(k); (5) bootstrap and jackknife spatial error estimation; (6) Claim 7 status and NT25 unification check. Primary tracer: eROSITA-DE DR1 cluster catalogue (erass1cl_main_v3.2.fits, NT28). Validation tracer: eROSITA-RU TDEs (NT29). API infrastructure adapted from external scripts (Perplexity AI and anonymous AI, May 2026); physical methodology from the COCM corpus.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Computational Physics and Python Applications
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