J/A+A/685/A107    Machine learning applications for AGN studies (Mechbal+, 2024)

Machine learning applications in studies of the physical properties of active galactic nuclei based on photometric observations. Mechbal S., Ackermann M., Kowalski M. <Astron. Astrophys. 685, A107 (2024)> =2024A&A...685A.107M 2024A&A...685A.107M (SIMBAD/NED BibCode)
ADC_Keywords: Active gal. nuclei; QSOs ; X-ray sources ; Photometry ; Accretion Keywords: accretion, accretion disks - methods: data analysis - catalogs - galaxies: active - galaxies: fundamental parameters - galaxies: photometry Abstract: We investigate the physical nature of active galactic nuclei (AGNs) using machine learning (ML) tools. We show that the redshift, z, bolometric luminosity, LBol, central mass of the supermassive black hole (SMBH), MBH, Eddington ratio, λEdd, and AGN class (obscured or unobscured) can be reconstructed through multi-wavelength photometric observations only. We trained a random forest regressor (RFR) ML-model on 7616 spectroscopically observed AGNs from the SPIDERS- AGN survey, which had previously been cross-matched with soft X-ray observations (from ROSAT or XMM), WISE mid-infrared photometry, and optical photometry from SDSS ugriz filters. We built a catalog of 21 050 AGNs that were subsequently reconstructed with the trained RFR; for 9687 sources, we found archival redshift measurements. All AGNs were classified as either type 1 or type 2 using a random forest classifier (RFC) algorithm on a subset of known sources. All known photometric measurement uncertainties were incorporated via a simulation-based approach. We present the reconstructed catalog of 21050 AGNs with redshifts ranging from 0<z<2.5. We determined z estimations for 11363 new sources, with both accuracy and outlier rates within 2%. The distinction between type 1 or type 2 AGN could be identified with respective efficiencies of 94% and 89%. The estimated obscuration level, a proxy for AGN classification, of all sources is given in the dataset. The LBol , MBH , and λEdd values are given for 21050 new sources with their estimated error. The release of this catalog will advance AGN studies by presenting key parameters of the accretion history of 6dex in luminosity over a wide range of z. Similar applications of ML techniques using photometric data only will be essential in the future, with large datasets from eROSITA, JSWT, and the VRO poised to be released in the next decade. Description: This catalog includes the 21050 reconstructed sources, with results from the obscuration classifier and estimation of z, LX, LBol, MBH, LEdd, and λEdd with associated reconstruction uncertainties. In addition, the 7613 SPIDERS sources used in the training sample are also included. A description of the catalog's columns is given below. Features providing X-ray, IR, and optical information are also given. File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file catalog.dat 842 28663 Positions, photometric magnitude and errors, redshift, reconstructed AGN physical parameters -------------------------------------------------------------------------------- See also: VII/258 : Quasars and Active Galactic Nuclei (13th Ed.) (Veron+ 2010) II/328 : AllWISE Data Release (Cutri+ 2013) IX/53 : XMM-Newton slew survey Source Catalogue, version 2.0 (XMM-SSC, 2017) J/A+A/588/A103 : Second ROSAT all-sky survey (2RXS) source catalog (Boller+, 2016) Byte-by-byte Description of file: catalog.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 6 A6 --- XName 2RXS or XMMSL2 X-ray detection (1) 8- 23 A16 --- Name X-ray identifier (JHHMMSS.s+DDMMSS) 25- 46 F22.18 deg RAdeg X-ray right ascension (J2000) 48- 70 E23.15 deg DEdeg X-ray declination (J2000) 72- 90 F19.15 [mW/m2] logFlux X-ray 0.5-2 keV band flux 92-115 E24.16 [mW/m2] e_logFlux ?=- X-ray 0.5-2 keV band flux error 119-137 A19 --- ALLWISE WISE All-Sky Release catalog name, JHHMMSS.ss+DDMMSS.s (2) 141-151 F11.7 deg RAWdeg AllWISE right ascension (J2000) 153-163 E11.3 deg DEWdeg AllWISE declination (J2000) 165-182 F18.15 mag W1mag AllWISE W1 magnitude (Vega) 184-201 F18.15 mag W2mag AllWISE W2 magnitude (Vega) 203-221 F19.16 mag W3mag AllWISE W3 magnitude (Vega) 223-241 F19.16 mag W4mag AllWISE W4 magnitude (Vega) 243-263 F21.19 mag e_W1mag AllWISE W1 magnitude error (Vega) 265-284 F20.18 mag e_W2mag AllWISE W2 magnitude error (Vega) 286-305 F20.18 mag e_W3mag AllWISE W3 magnitude error (Vega) 307-326 F20.18 mag e_W4mag AllWISE W4 magnitude error (Vega) 328-349 F22.15 e/s FG Gaia G mean flux 351-371 F21.16 e/s e_FG Gaia G mean flux error 373-379 A7 --- Class Broad spectral classification computed by the SDSS-DR16 spectroscopic pipeline 383-403 A21 --- SubClass Detailed spectral classification computed by the SDSS-DR16 spectroscopic pipeline 406-413 F8.5 mag umagPSF SDSS PSF magnitude in the u-band (AB) 415-422 F8.5 mag gmagPSF SDSS PSF magnitude in the g-band (AB) 424-431 F8.5 mag rmagPSF SDSS PSF magnitude in the r-band (AB) 433-440 F8.5 mag imagPSF SDSS PSF magnitude in the i-band (AB) 442-449 F8.5 mag zmagPSF SDSS PSF magnitude in the z-band (AB) 451-463 F13.9 mag e_umagPSF SDSS PSF magnitude error in the u-band (AB) 465-478 E14.6 mag e_gmagPSF SDSS PSF magnitude error in the g-band (AB) 480-493 E14.6 mag e_rmagPSF SDSS PSF magnitude error in the r-band (AB) 495-508 E14.6 mag e_imagPSF SDSS PSF magnitude error in the i-band (AB) 510-521 F12.9 mag e_zmagPSF SDSS PSF magnitude error in the z-band (AB) 523-546 E24.16 --- z Redshift of the source 548-568 F21.19 --- e_z Uncertainty in the redshift 570-587 F18.15 [10-7W] logLX X-ray luminosity in the 0.5-2keV band 589-611 E23.15 [10-7W] e_logLX ?=- Uncertainty on the X-ray luminosity in the 0.5-2keV band 613-630 F18.15 [10-7W] logLbol Bolometric luminosity 632-655 E24.16 [10-7W] e_logLbol Uncertainty on the bolometric luminosity 657-675 F19.16 [Msun] logMBH Black hole mass 677-700 E24.16 [Msun] e_logMBH Uncertainty on the black hole mass 702-719 F18.15 [10-7W] logLEdd Eddington luminosity 721-744 E24.16 [10-7W] e_logLEdd ?=- Uncertainty on the Eddington luminosity 746-767 E22.14 [-] logREdd Eddington ratio 769-791 E23.15 [-] e_logREdd ?=- Uncertainty on the uncertainty 793 I1 --- Recons [0/1]? Flag indicating whether the source and values from columns (z to e_logEddRatio) are from (3) 795 I1 --- knownz [0/1]? Flag indicating whether the redshift values (z and e_z) come from (4) 797-820 E24.16 --- obscur [0/1] Value between 0 and 1 indicating whether the source is obscured (obscuration ∼ 1) or not (obscuration ∼ 0), from the ML classifier 822-842 F21.19 --- e_obscur Uncertainty on the obscuration value -------------------------------------------------------------------------------- Note (1): For 2RXS, Boller et al., 2016A&A...588A.103B 2016A&A...588A.103B, Cat. J/A+A/588/A103, for XMMSL2, XMM-SSC, 2017, Cat. IX/53. Note (2): From AllWISE, 2013, Cat. II/328. Note (3): Flag as follows: 0 = from SPIDERS AGN spectroscopic catalog, Coffey et al., 2019A&A...625A.123C 2019A&A...625A.123C 1 = from this work's ML reconstruction Note (4): Flag as follows: 0 = from this work's ML reconstruction 1 = from Dwelly et al., 2017MNRAS.469.1065D 2017MNRAS.469.1065D or Veron-cetty & Veron, 2010A&A...518A..10V 2010A&A...518A..10V, Cat. VII/258 -------------------------------------------------------------------------------- Acknowledgements: Sarah Mechbal, sarah.mechbal(at)desy.de
(End) Patricia Vannier [CDS] 16-Feb-2024
The document above follows the rules of the Standard Description for Astronomical Catalogues; from this documentation it is possible to generate f77 program to load files into arrays or line by line