Periodic Reporting for period 1 - ML-SMBH (Multifrequency and Machine Learning methods to Search for Early Super Massive Black Holes)
Reporting period: 2022-12-01 to 2025-01-31
This project aimed to leverage multifrequency astrophysical data to identify high-redshift blazars and quasars, essential for exploring the early Universe and the Epoch of Reionization (EoR). The goal was to uncover new high-redshift jetted supermassive black holes (SMBHs), guiding observational campaigns, directly contributing to understanding galaxy evolution and SMBH growth during the EoR.
The PI developed a multifrequency data frame representative of blazars detected from radio up to gamma-rays, creating the First Cosmic Gamma-ray Horizon (1CGH) catalogue. The catalogue nearly doubled the number of sources detected above 10 GeV and is now accepted for publication in MNRAS. The 1CGH catalogue allows precise measurements of Extragalactic Background Light (EBL) density up to z ~ 3.2 enabling accurate estimates of star formation rates (SFR) at high redshifts (z ~ 6-7), within the EoR. A critical gap was addressed, revealing that 72% of the sources lack robust redshift characterization, thus strategically guiding future observational efforts. The resulting multifrequency dataframe will be publicly available on Vizier.
Additionally, a sample of high-z jetted quasars was selected using data from the radio Rapid ASKAP Continuum Survey (RACS) combined with deep wide-area optical/near-infrared surveys. This resulted in selecting 45 new high-z radio quasar candidates, 24 spectroscopically confirmed, including 11 at z >5. Results published in "High-z radio Quasars in RACS I: Selection, identification, and multi-wavelength properties” (accepted in A&A) significantly update the density estimate of jetted SMBH at high redshift.
Throughout this project, the PI actively focused on machine learning (ML) methods and astrophysical data handling, conducting educational initiatives at the Institute of Astrophysics (IA) in Lisbon, teaching multifrequency data analysis and ML applied to astrophysics to PhD, MSc, and internship students. These efforts notably resulted in developing an ML photometric model capable of predicting quasar redshifts up to z~7.5. This model can efficiently identify high-redshift quasar candidates and inform observational campaigns.
Furthermore, leveraging expertise in gamma-ray analysis, the PI explored heliophysics, discovering unexpected anisotropy and temporal variability in gamma-ray emissions from the solar disk during the 2014 solar maximum. This groundbreaking result led to a highly impactful publication in the Astrophysical Journal (ApJ) and extensive media coverage, significantly exceeding the project's original expectations.
The PI developed a multifrequency data frame representative of blazars detected from radio up to gamma-rays, creating the First Cosmic Gamma-ray Horizon (1CGH) catalogue. The catalogue nearly doubled the number of sources detected above 10 GeV and is now accepted for publication in MNRAS. The 1CGH catalogue allows precise measurements of Extragalactic Background Light (EBL) density up to z ~ 3.2 enabling accurate estimates of star formation rates (SFR) at high redshifts (z ~ 6-7), within the EoR. A critical gap was addressed, revealing that 72% of the sources lack robust redshift characterization, thus strategically guiding future observational efforts. The resulting multifrequency dataframe will be publicly available on Vizier.
Additionally, a sample of high-z jetted quasars was selected using data from the radio Rapid ASKAP Continuum Survey (RACS) combined with deep wide-area optical/near-infrared surveys. This resulted in selecting 45 new high-z radio quasar candidates, 24 spectroscopically confirmed, including 11 at z >5. Results published in "High-z radio Quasars in RACS I: Selection, identification, and multi-wavelength properties” (accepted in A&A) significantly update the density estimate of jetted SMBH at high redshift.
Throughout this project, the PI actively focused on machine learning (ML) methods and astrophysical data handling, conducting educational initiatives at the Institute of Astrophysics (IA) in Lisbon, teaching multifrequency data analysis and ML applied to astrophysics to PhD, MSc, and internship students. These efforts notably resulted in developing an ML photometric model capable of predicting quasar redshifts up to z~7.5. This model can efficiently identify high-redshift quasar candidates and inform observational campaigns.
Furthermore, leveraging expertise in gamma-ray analysis, the PI explored heliophysics, discovering unexpected anisotropy and temporal variability in gamma-ray emissions from the solar disk during the 2014 solar maximum. This groundbreaking result led to a highly impactful publication in the Astrophysical Journal (ApJ) and extensive media coverage, significantly exceeding the project's original expectations.
- Jetted SMBHs as cosmic probes: The “Mapping the Cosmic Gamma‑ray Horizon” study delivers the 1CGH catalogue, with 2791 Fermi‑LAT detections above 10 GeV (62 new) extracted from 16 yr of data. For every source we compute the mean energy of its four highest‑energy photons and compare it with EBL models, isolating 525 objects that show moderate‑to‑severe absorption (0 < z < 3). An overview of ~70 papers with results from optical observation campaigns allowed redshift updates, but 72 % of the 1CGH sample still lacks robust z, highlighting the need for targeted spectroscopy. We publish a priority list of: (i) objects with no z but solid radio/optical IDs, ranked by highest detected energy; (ii) objects with tentative z or lower limits, ranked by τ(E,z).
These targets will refine EBL density measurements and tighten SFR density at z ≈ 6‑7, well within the EoR, settling gamma-ray blazars as complementary probes of galaxy evolution along cosmic time.
- High‑z radio quasars: 45 candidates selected from ASKAP‑RACS + optical/NIR; spectroscopy confirms 24, including 11 at z > 5 (paper accepted in A&A). This doubles the census of radio‑loud quasars beyond z > 5 and provides an improved sample for jetted-SMBH growth studies.
- ML Photo-z in 0 < z < 7.5 range: A ML model trained on WISE + SDSS photometry successfully predicts quasar redshifts across a vast range and flags rare z ≈ 7 candidates. Feature‑importance has the potential to yield colour cuts that can be applied to IR-to-Optical catalogues and guide the search of EoR quasars.
- Solar gamma‑ray discovery: Analysis led by the PI revealed a polar GeV excess during the 2014 solar maximum (ApJ, 2024). The result links gamma‑ray morphology to solar activity, challenges existing emission models and argues for real‑time GeV solar-monitoring on future gamma-ray missions. Insights gained during the ongoing 2025 maximum could bring new elements to our solar-activity forecasting capabilities.
- High‑z radio quasars: 45 candidates selected from ASKAP‑RACS + optical/NIR; spectroscopy confirms 24, including 11 at z > 5 (paper accepted in A&A). This doubles the census of radio‑loud quasars beyond z > 5 and provides an improved sample for jetted-SMBH growth studies.
- ML Photo-z in 0 < z < 7.5 range: A ML model trained on WISE + SDSS photometry successfully predicts quasar redshifts across a vast range and flags rare z ≈ 7 candidates. Feature‑importance has the potential to yield colour cuts that can be applied to IR-to-Optical catalogues and guide the search of EoR quasars.
- Solar gamma‑ray discovery: Analysis led by the PI revealed a polar GeV excess during the 2014 solar maximum (ApJ, 2024). The result links gamma‑ray morphology to solar activity, challenges existing emission models and argues for real‑time GeV solar-monitoring on future gamma-ray missions. Insights gained during the ongoing 2025 maximum could bring new elements to our solar-activity forecasting capabilities.
The results obtained during this fellowship significantly advanced knowledge in various astrophysical domains. The creation of the First Cosmic Gamma-ray Horizon (1CGH) catalogue marks a significant advancement in extragalactic multifrequency astronomy. Using an extended dataset (16 years of Fermi-LAT data), this work achieved an ~80% increase in gamma-ray source detections above 10 GeV, including 62 previously unknown sources. This unique sample will support follow-up studies by next-generation gamma-ray telescopes such as the Cherenkov Telescope Array Observatory (CTAO). A comprehensive redshift review (including 70 observational campaigns) showed that 72% of the 1CGH catalogue still lacks robust redshift data, highlighting future observational opportunities crucial for measuring Star Formation Rates (SFR) at high redshifts (z~6-7). The catalogue also revealed multiple unexpected gamma-ray detections above opacity limits, suggesting a need to reassess our current understanding of the Cosmic Gamma-Ray Horizon (CGH).
The identification of high-redshift quasars using ASKAP RACS data advanced our understanding of early Universe radio-bright quasars. Combining RACS with deep optical/NIR surveys, 45 new high-z candidates were identified over 16,000 square degrees, with spectroscopic confirmation for 24 quasars, including 11 at z > 5. Most have jets oriented close to our line of sight, providing a valuable statistical sample of extremely luminous early quasars, and updated density estimate for jetted-SMBH at early Universe.
The development of a Machine Learning (ML) model predicting quasar redshifts from photometric data showed promising accuracy across 0 < z < 7.5. This ML model can effectively highlight high-redshift candidates, optimizing observational campaigns to target rare, high-z quasars, crucial for exploring the EoR.
The discovery of unexpected solar gamma-ray emission asymmetry challenges established models. Evidence of excess polar gamma-ray emissions during the 2014 solar maximum has implications for solar physics, suggesting GeV solar monitoring can potentially improve our ability to forecast solar storms and space weather. This impactful finding has garnered considerable attention from both the scientific community and the media.
The identification of high-redshift quasars using ASKAP RACS data advanced our understanding of early Universe radio-bright quasars. Combining RACS with deep optical/NIR surveys, 45 new high-z candidates were identified over 16,000 square degrees, with spectroscopic confirmation for 24 quasars, including 11 at z > 5. Most have jets oriented close to our line of sight, providing a valuable statistical sample of extremely luminous early quasars, and updated density estimate for jetted-SMBH at early Universe.
The development of a Machine Learning (ML) model predicting quasar redshifts from photometric data showed promising accuracy across 0 < z < 7.5. This ML model can effectively highlight high-redshift candidates, optimizing observational campaigns to target rare, high-z quasars, crucial for exploring the EoR.
The discovery of unexpected solar gamma-ray emission asymmetry challenges established models. Evidence of excess polar gamma-ray emissions during the 2014 solar maximum has implications for solar physics, suggesting GeV solar monitoring can potentially improve our ability to forecast solar storms and space weather. This impactful finding has garnered considerable attention from both the scientific community and the media.