Kavli Affiliate: Risa Wechsler
| Summary:
Quasars acting as strong gravitational lenses offer a rare opportunity to probe the redshift evolution of scaling relations between supermassive black holes and their host galaxies, particularly the $M_mathrmBH$–$M_mathrmhost$ relation. Using these powerful probes, the mass of the host galaxy can be precisely inferred from the Einstein radius $θ_mathrmE$. Using 812,118 quasars from DESI DR1 ($0.03 leq z leq 1.8$), we searched for quasars lensing higher-redshift galaxies by identifying background emission-line features in their spectra. To detect these rare systems, we trained a convolutional neural network (CNN) on mock lenses constructed from real DESI spectra of quasars and emission-line galaxies (ELGs), achieving a high classification performance (AUC = 0.99). We also trained a regression network to estimate the redshift of the background ELG. Applying this pipeline, we identified seven high-quality (Grade~A) lens candidates, each exhibiting a strong [O,textscii] doublet at a higher redshift than the foreground quasar; four candidates additionally show H$β$ and [O,textsciii] emission. These results significantly expand the sample of quasar lens candidates beyond the twelve identified and three confirmed in previous work, and demonstrate the potential for scalable, data-driven discovery of quasars as strong lenses in upcoming spectroscopic surveys.
| Search Query: arXiv Query: search_query=au:”Wechsler Risa”&id_list=&start=0&max_results=10
Read More