Abstract
We present the selection techniques based on the use of Neural Networks and on the cross match between FIRST and SDSS that lead to the spectroscopic identification of 15 new Radio Loud QSOs in the redshift range 3. 6 ≤ z ≤ 4. 4. These QSOs did not have previous spectroscopical identification in SDSS or other works. Our selection method is highly complete (97 %) and it allows the estimation of the binned luminosity function of radio-loud quasar at \(z \sim 4\) with unprecedented accuracy. Our luminosity function is compared with the results of other samples of RL QSOs in similar ranges of redshift and with the whole population of QSOs (RL+RQ). The evolution of the luminosity function with redshift was for many years interpreted as a flattening of the bright end slope, but has recently been re-interpreted as strong evolution of the break luminosity for high-z QSOs and our results, for the radio-loud population, are consistent with this. We also find indications of a constant radio-loud fraction for QSOs at high z. Our next investigation will select RL QSOs candidates in the range of redshift 4. 4 ≤ z ≤ 5. 7, and will make use of data in the radio (FIRST), in the optical (SDSS DR10) and in the infrared (UKIDSS Large Area Survey DR10, and WISE).
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Tuccillo, D., González-Serrano, J.I., Benn, C.R. (2016). Selection of High-z Radio-Loud Quasars, and Their Luminosity Function. In: Napolitano, N., Longo, G., Marconi, M., Paolillo, M., Iodice, E. (eds) The Universe of Digital Sky Surveys. Astrophysics and Space Science Proceedings, vol 42. Springer, Cham. https://doi.org/10.1007/978-3-319-19330-4_45
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DOI: https://doi.org/10.1007/978-3-319-19330-4_45
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