Prospects for probing supermassive binary black holes in strongly lensed active galactic nuclei via microlensing effects
arXiv:2611.15056 · doi:10.1007/s11433-026-3100-3
Abstract
Gravitational microlensing in strongly lensed active galactic nuclei (AGNs) provides a powerful probe of accretion-disk structure and may offer a unique opportunity to identify sub-parsec supermassive binary black holes (SMBBHs) through distinctive signatures. Upcoming wide-field surveys are expected to discover a large sample of strongly lensed AGNs, a fraction of which may host SMBBHs detectable via microlensing. In this paper, we employ semi-analytic models to assess the detection prospects of sub-parsec SMBBHs in lensed AGNs, focusing on systems with resolvable multiple images suitable for microlensing analysis. Accounting for galaxy-scale strong-lensing statistics, and including the cluster-lensing contribution as an optimistic statistical extension, we estimate that up to approximately 87 such systems could be spatially resolved by individual upcoming surveys, including the Vera C. Rubin Observatory (Rubin), Euclid, China's Space Survey Telescope (CSST), and the Roman. For the Rubin WFD survey, we estimate that periodic oscillations in microlensing light curves could identify short-period (\,yr) binaries, whereas diagnostics based on the reconstructed size-wavelength relation apply to a broader population, potentially identifying systems, depending on the model assumptions. CSST, Euclid, and Roman may also reveal up to , , and systems exhibiting size-wavelength features, and , , systems showing periodic oscillations, which should be regarded as imaging-selected candidates whose microlensing-based identification requires adequate time-domain follow-up, including cadence, monitoring baseline, photometric precision, and reliable time-delay measurements. Our results show that strongly lensed AGNs provide a promising, though observationally demanding, pathway for finding candidate SMBBHs via microlensing.
arXiv comment10 pages, 8 figures
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