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June 1, 20260 citationsOpen Access

NT30: COCM Route 3 Analysis Pipeline — Complete Python Implementation

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JGJosé Luis Vázquez González

Key Points

  • The aim is to implement a Python pipeline for analyzing COCM Route 3 parameters and testing specific claims regarding unification conditions.
  • Developed a COCMPhysics class including corpus constants and relations.
  • Implemented comoving coordinate conversion and survey mask generation for eROSITA surveys.
  • Applied Landy-Szalay xi(r) estimator and conducted spatial error estimation using bootstrap and jackknife methods.
  • Successfully implemented a pipeline for calculating ratios and validating unification conditions.
  • Achieved accurate spatial error estimates indicating high reliability of measurements.
  • Validated the primary tracer using eROSITA-DE data and assessed Claim 7 for status relevance.

Abstract

Complete Python implementation of the COCM Route 3 analysis pipeline for measuring I = P (2kCOCM) /P (kCOCM) and eI = (I/1910) ^ (1/4. 86) (NT25), testing Claim 7 (e > 0) and the NT25 unification condition ePA = eJ = eI. The pipeline implements: (1) COCMPhysics class with all corpus constants and relations (kCOCM = 0. 003 Mpc^-1, I₀ = 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 (erass1clₘainᵥ3. 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.

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Cite This Study

José Luis Vázquez González (2026) studied this question.

synapsesocial.com/papers/6a1d22db02fbce91306388b4https://doi.org/10.5281/zenodo.20464646
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