{"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/characterizing-the-observation-bias-in","title":"Characterizing the observation bias in gravitational-wave detections and finding structured population properties","arxiv_id":"2105.13983","date":"2021-05-28","proceeding":null,"authors":["Doğa Veske","Imre Bartos","Zsuzsa Márka","Szabolcs Márka"],"abstract":"The observed distributions of the source properties from gravitational-wave detections are biased due to the selection effects and detection criteria in the detections, analogous to the Malmquist bias. In this work, this observation bias is investigated through its fundamental statistical and physical origins. An efficient semi-analytical formulation for its estimation is derived which is as accurate as the standard method of numerical simulations, with only a millionth of the computational cost. Then, the estimated bias is used for unmodelled inferences on the binary black hole population. These inferences show additional structures, specifically two peaks in the joint mass distribution around binary masses $\\sim10$ M$_\\odot$ and $\\sim30$ M$_\\odot$. Example ready-to-use scripts and some produced datasets for this method are shared in an online repository.","url_abs":"https://arxiv.org/abs/2105.13983v2","url_pdf":"https://arxiv.org/pdf/2105.13983v2.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":"characterizing-the-observation-bias-in","repo_url":"https://github.com/dveske/observation-bias-gw","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}