SOURCE-LINKED INTELLIGENCE
Multifrequency and Machine Learning methods to Search for Early Super Massive Black Holes
Multifrequency and Machine Learning methods to Search for Early Super Massive Black Holes 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
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 172618.56
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T00:21:03.701Z. This is not the publication date.