Project description
Machine learning could aid in the detection of high-redshift blazars
A blazar is a feeding supermassive black hole in the centre of a distant galaxy and emits extremely powerful relativistic jets in the direction of Earth. To date, few blazars known to have a redshift (z) larger than 4 have been discovered. The search for high-redshift blazars is essential to put a strong constraint on the lower density limit of relativistic jets from supermassive black holes close and during the Epoch of Reionisation. Funded by the Marie Skłodowska-Curie Actions programme, the ML-SMBH project will facilitate the discovery of high-redshift blazar candidates using machine learning techniques. In particular, researchers will study possible high-redshift blazar (z>7) candidates based on data from Lyman-alpha damping wing absorption, which should provide a remarkable view into the early universe.
Objective
Early Super Massive Black Holes (SMBH) continuously push our understanding of the formation of galaxies and structures in the Universe. SMBH accreting matter under the radio/jet mode produces powerful relativistic jets and emit beamed non-thermal radiation from radio up to very high energy gamma-rays. Those jets pointing directly to Earth create the so-called Blazar phenomena, where the source appears exceptionally bright due to relativistic magnification (beaming) effects. We can spot Blazars up to high redshifts, but they are rare (given the geometrical alignment constraints involved). To date, only a few distant blazars are known (e.g. QJ0906+6930 z=5.57 and PSO J030947+271757 z=6.1) and a direct search for new ones is impactful because each source at z > 5 implies the existence of thousands of similar misaligned objects. A systematic investigation at z > 5-6 will provide a robust lower limit for the density of Jetted SMBH close and within the Epoch of Reionization (EoR). This research proposal aims to apply Machine Learning (ML) techniques coupled with Multifrequency data to search for high redshift blazars candidates. We plan to select promising z~7 candidates based on the Damping Wing Pattern (DWP). The DWP manifests as the absorption of the observed wavelength λ < 970nm (<121nm, rest-frame) due to neutral gas in the intergalactic medium (IGM) at z > 7 and is very sensitive to the neutral fraction of the IGM. The DWP allows to probe well within the EoR phase and provide a remarkable view into the early Universe. This proposal will leverage fresh survey releases (as the CatWISE2020 in IR and eROSAT Q4-2022 in X-rays) and benefit from the leading role of Instituto de Astrofísica (IA) within ASKAP and MOONS projects (which will provide deep radio data and support for optical observations). This plan will apply ML to a complex Multifrequency data frame in search of high-redshift sources and contribute to establishing the fast-emerging branch of Astroinformatics.
Fields of science
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-AG-UN - HORIZON Unit GrantCoordinator
1749 016 Lisbon
Portugal