A property-matched search for cosmic topology: analysis code and data products (DESI DR1 quasars)

Analysis code and data products supporting the paper "A property-matched search for cosmic topology: validated framework and first constraints from 1.45 million DESI DR1 quasars" (N. Balyan). If the Universe is multiply connected, the same quasar can appear at several sky positions. This package contains the complete pipeline behind a search for such repeat images in 1,452,003 spectroscopically confirmed DESI DR1 quasars (0.8 < z < 3.5), together with the injection-recovery framework that validates it on all ten compact flat 3-manifolds (E1-E10) and converts the null result into exclusion limits, including the first observational bounds on the non-orientable Klein-type manifolds E7-E10. Contents:- code/ : 16 Python analysis scripts (Python >= 3.11; numpy, scipy, matplotlib, astropy). Every quantitative claim in the paper regenerates from these scripts with fixed random seeds; a script-to-section table is given in the README.- data/ : input catalogues and derived products, including the DESI DR1 quasar working catalogue (from the healpix-coadd redshift catalogue, DESI Collaboration 2025, arXiv:2503.14745, retrieved via the NOIRLab Astro Data Lab TAP service; CC BY 4.0), the empirical identity-noise pool measured from 42,355 repeat-observation pairs, SPARC and Yale Bright Star Catalogue extracts (via VizieR), and JADES DR3 NIRSpec prism line-flux catalogues (via MAST).- figures/ : all paper figures and the numerical results (JSON) they are drawn from. The DESI DR1 quasar-pair catalogue of Jing et al. (2025, arXiv:2505.03103), used for one comparison in the paper, is not redistributed here; the README explains where to obtain it. All analyses run offline from the included data; network access is needed only by the fetch scripts. See README.md inside the archive for the full layout, reproduction table, provenance list and usage examples. Licensing: code is released under the MIT license; derived data products under CC BY 4.0 with attribution to the underlying surveys as listed in the README.