Predicting Quasar Counts Detectable in the LSST Survey

Abstract The Legacy Survey of Space and Time (LSST), being conducted by the Vera C. Rubin Observatory, is a wide-field multiband survey that will revolutionize our understanding of extragalactic sources through its unprecedented combination of area and depth. While the LSST survey strategy is still being finalized, the Rubin Observatory team has generated a series of survey simulations using the LSST Operations Simulator to explore the optimal survey strategy that best accommodates the majority of scientific goals. In this study, we utilize the latest simulated data and the Metrics Analysis Framework to predict the number of quasars detectable by LSST in each band and evaluate the impact of different survey strategies. We find that the number of quasars and lower-luminosity active galactic nuclei (AGNs) detected in the baseline strategy (v4.3.1) in the redshift range z = 0.3–6.7 will be highest in the i band (about 12 million) and lowest in the u band (about 6 million). Over 70% of quasars are expected to be detected within the first year in all bands, as LSST will have already reached the break in the luminosity function at most redshifts. With a limiting magnitude of 25.7 (26.9) mag, we expect to detect 184 (199) million AGNs in the z band ( r band) over the 10 yr survey, with quasars constituting only 6% of the total AGNs in each band. This arises because, considering that the luminosities of most low-luminosity AGNs are affected by contamination from their host galaxies, we set a magnitude threshold when predicting the number of quasars. We find that variations in the u -band strategy can impact the number of quasar detections. Specifically, the difference between the baseline strategy and that with the largest total exposure in u is 15%. In contrast, changes in rolling strategies, Deep Drilling Field strategies, weather conditions, and Target of Opportunity observations result in variations below 2%. These results provide valuable insights for optimizing approaches to maximize the scientific output of quasar studies.