Abstract

High-redshift (z>5) quasars have an important role in galaxy formation and evolution, including the growth of supermassive black holes, the coevolution of black holes and galaxies, and changes in the ionization state of the Universe. However, conventional methods for identifying high redshift quasars face challenges like high false-positive rates and require resource-intensive spectroscopic follow-up. With the upcoming data influx from optical deep wide area. imaging surveys like Vera Rubin Observatory Legacy Survey of Space and Time (LSST), the need for more efficient methodologies becomes crucial. This presentation introduces a new approach to identifying and characterising high-redshift quasars via optical and infrared Spectral Energy Distribution (SED) fitting, with an emphasis on reliable photometric redshifts. Our SED fitting method characterises quasar candidates by redshift, host galaxy contribution, intrinsic reddening, and luminosity. Additionally, we present a new empirical model for intergalactic hydrogen absorption. By comparing fits between quasar, galaxy, and star models, we are able to reduce rates of foreground contamination. The methodology presented shows promise in identifying quasar candidates and validating known objects, presenting an efficient avenue for discoveries and insights into the early Universe.