High redshift radio-loud quasars in large-area surveys
ABSTRACT: Around 8-13\% of the known population of quasars (QSOs) are powerful radio emitter and therefore classified as Radio-Loud (RL), while the remaining part is classified as Radio-Quiet (RQ). The reason of the radio emission is explained in terms of the presence of a radio-jet, responsible for...
| Autor: | |
|---|---|
| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/8132 |
| Acceso en línea: | http://hdl.handle.net/10902/8132 |
| Access Level: | acceso abierto |
| Palabra clave: | Astronomía y Astrofísica Análisis de datos Espectroscopia astrofísica Inteligencia artificial |
| Sumario: | ABSTRACT: Around 8-13\% of the known population of quasars (QSOs) are powerful radio emitter and therefore classified as Radio-Loud (RL), while the remaining part is classified as Radio-Quiet (RQ). The reason of the radio emission is explained in terms of the presence of a radio-jet, responsible for the synchrotron emission and relativistic particles in intense magnetic fields. Nevertheless, the reason why only a minority of the quasars show strong radio-emission and which is the physical connection between these two major classes of objects, still lack a convincing explanation. Quasars are relatively rare, especially at high redshift, since their comoving density is a strong function of redshift that peaks at z~2-3 and declines exponentially at higher redshifts. The radio-loud quasar population at z > 3.5 is an even more elusive population, therefore does not allow exhaustive statistical studies and comparisons between radio-loud and radio-quiet populations in the early universe, where it might be possible to gather clues on the connection between radio and optical activity in QSOs. The quest to increase the number of known radio-loud quasars at high redshift require the use of large area surveys, advanced techniques of data mining to deal with the sheer volume of data of modern surveys, and the refinement of the candidate-selection techniques to select quasar-candidate of potential interest from broad-band photometric surveys. This thesis is focused on the selection and study of high-redshift RL QSOs at z>3.6. We combined modern data mining techniques and machine-learning algorithms for an efficient and complete exploitation of multi-wavelength data from large-area surveys in the optical (SDSS), in the near- and mid-infrared (UKIDSS, WISE) and in the radio (FIRST). We completed and tested our modern techniques of analysis and selection through follow-up optical spectroscopy and radio observations of the samples of RL quasars of our interest. We analyzed the results of our observations and drew conclusions both on the techniques used for the candidate-selection and on the physics of the studied objects. |
|---|