{"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/photometric-selection-of-type-1-quasars-in","title":"Photometric Selection of type 1 Quasars in the XMM-LSS Field with Machine Learning and the Disk-Corona Connection","arxiv_id":"2412.06923","date":"2024-12-09","proceeding":null,"authors":["Jian Huang","Bin Luo","W. N. Brandt","Ying Chen","Qingling Ni","Yongquan Xue","Zijian Zhang"],"abstract":"We present photometric selection of type 1 quasars in the $\\approx5.3~{\\rm deg}^{2}$ XMM-Large Scale Structure (XMM-LSS) survey field with machine learning. We constructed our training and \\hbox{blind-test} samples using spectroscopically identified SDSS quasars, galaxies, and stars. We utilized the XGBoost machine learning method to select a total of 1\\,591 quasars. We assessed the classification performance based on the blind-test sample, and the outcome was favorable, demonstrating high reliability ($\\approx99.9\\%$) and good completeness ($\\approx87.5\\%$). We used XGBoost to estimate photometric redshifts of our selected quasars. The estimated photometric redshifts span a range from 0.41 to 3.75. The outlier fraction of these photometric redshift estimates is $\\approx17\\%$ and the normalized median absolute deviation ($\\sigma_{\\rm NMAD}$) is $\\approx0.07$. To study the quasar disk-corona connection, we constructed a subsample of 1\\,016 quasars with HSC $i<22.5$ after excluding radio-loud and potentially X-ray-absorbed quasars. The relation between the optical-to-X-ray power-law slope parameter ($\\alpha_{\\rm OX}$) and the 2500 Angstrom monochromatic luminosity ($L_{2500}$) for this subsample is $\\alpha_{\\rm OX}=(-0.156\\pm0.007)~{\\rm log}~{L_{\\rm 2500}}+(3.175\\pm0.211)$ with a dispersion of 0.159. We found this correlation in good agreement with the correlations in previous studies. We explored several factors which may bias the $\\alpha_{\\rm OX}$-$L_{\\rm 2500}$ relation and found that their effects are not significant. We discussed possible evolution of the $\\alpha_{\\rm OX}$-$L_{\\rm 2500}$ relation with respect to $L_{\\rm 2500}$ or redshift.","url_abs":"https://arxiv.org/abs/2412.06923v1","url_pdf":"https://arxiv.org/pdf/2412.06923v1.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":"photometric-selection-of-type-1-quasars-in","repo_url":"https://github.com/choubalv-hj/AstroML","is_official":1,"mentioned_in_paper":0,"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}