Variability in the supermassive black hole binary candidate SDSS J2320+0024: No evidence of periodic modulation
Fabio Rigamonti, Lorenzo Bertassi, Riccardo Buscicchio, Fabiola Cocchiararo, Stefano Covino, Massimo Dotti, Alberto Sesana, and Paola Severgnini

TL;DR
This study reanalyzed the variability of the SBHB candidate SDSS J2320+0024, finding no statistically significant evidence of periodic modulation and highlighting the importance of rigorous statistical methods in such analyses.
Contribution
The paper provides a comprehensive Bayesian reanalysis of the light curves, challenging previous claims of periodicity and emphasizing the need for robust statistical validation in SBHB candidate studies.
Findings
No significant periodicity detected in g, r, i bands.
Broad posterior peaks do not favor periodic models over red noise.
Previous periodicity claims are not statistically supported.
Abstract
Supermassive black hole binaries (SBHBs) are a natural outcome of galaxy mergers, and they are expected to be among the loudest gravitational-wave sources at low frequencies. The source SDSS J2320+0024 was recently proposed as a promising SBHB candidate due to a possible periodicity in its light curve and variability in the MgII emission line. In this work, we reanalysed the optical (g, r, and i bands) light curves of J2320+0024 within the framework of Bayesian model selection. When periodicity was searched for together with red noise, analysis of the g-band light curve reveals a peak in the posterior of the period at ~290 days. The posterior profile is too broad to yield a preference for periodic models over models that include only red noise. Furthermore, the same peak is not present in the analysis of the r-band and i-band light curve. A periodic model without red noise identified a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
