{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/self-calibration-of-photometric-redshift","title":"Self-calibration of photometric redshift scatter from DECaLS DR8 power spectrum and validation with simulated catalogues","arxiv_id":"2203.14609","date":"2022-03-28","proceeding":null,"authors":["Hui Peng","Haojie Xu","Le Zhang","Zhao Chen","Yu Yu"],"abstract":"The uncertainty in the photometric redshift estimation is one of the major systematics in weak lensing cosmology. The self-calibration method is able to reduce this systematics without assuming strong priors. We improve the recently proposed self-calibration algorithm to enhance the stability and robustness with the noisy measurement. The improved algorithm is tested on the power spectra measured from the simulated catalogues constructed according to DECaLS DR8 photometric catalogue. For the fiducial analysis with 5 equal-width redshift bins over $0<z<1$ and 6 bands over scales $100 \\leq \\ell<1000$, we find that the improved algorithm successfully reconstructs the scatter rates and the auto power spectrum in true redshift bins at the level of $\\sim0.015$ and $\\sim4.4$ per cent, respectively. The bias of the mean redshift is reduced by more than 50 per cent compared to the photo-$z$ without self-calibration, especially for the cases with catastrophic photo-$z$ errors. The reconstructed results of DECaLS DR8 galaxy sample are in line with the expectations from the simulation validation. The self-calibration code is publicly available at https://github.com/PengHui-hub/FP-NMF.","url_abs":"https://arxiv.org/abs/2203.14609v2","url_pdf":"https://arxiv.org/pdf/2203.14609v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"self-calibration-of-photometric-redshift","repo_url":"https://github.com/penghui-hub/fp-nmf","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}