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Euclid preparation. XLIX. Selecting active galactic nuclei using observed colours

Euclid preparation. XLIX. Selecting active galactic nuclei using observed colours
Euclid preparation. XLIX. Selecting active galactic nuclei using observed colours
The Euclid space mission will cover over 14 000 deg2 with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution in general, and AGN in particular. For this work we identified the best colour selection criteria for AGN, based only on Euclid photometry or including ancillary photometric observations, such as the data that will be available with the Rubin Legacy Survey of Space and Time (LSST) and observations already available from Spitzer/IRAC. The analysis was performed for unobscured AGN, obscured AGN, and composite (AGN and star-forming) objects. We made use of the spectro-photometric realisations of infrared-selected targets at all-z (SPRITZ) to create mock catalogues mimicking both the Euclid Wide Survey (EWS) and the Euclid Deep Survey (EDS). Using these mock catalogues, we estimated the best colour selection, maximising the harmonic mean (F1) of: (a) completeness, that is, the fraction of AGN correctly selected with respect to the total AGN sample; and (b) purity, that is, the fraction of AGN inside the selection with respect to the selected sample. The selection of unobscured AGN in both Euclid surveys (Wide and Deep) is possible with Euclid photometry alone with F1 = 0.22–0.23 (Wide and Deep), which can increase to F1 = 0.43–0.38 (Wide and Deep) if we limit out study to objects at z > 0.7. Such a selection is improved once the Rubin/LSST filters, that is, a combination of the u, g, r, or z filters, are considered, reaching an F1 score of 0.84 and 0.86 for the EDS and EWS, respectively. The combination of a Euclid colour with the [3.6]−[4.5] colour, which is possible only in the EDS, results in an F1 score of 0.59, improving the results using only Euclid filters, but worse than the selection combining Euclid and LSST colours. The selection of composite (fAGN = 0.05–0.65 at 8–40 μm) and obscured AGN is challenging, with F1 ≤ 0.3 even when including Rubin/LSST or IRAC filters. This is unsurprising since it is driven by the similarities between the broad-band spectral energy distribution of these AGN and star-forming galaxies in the wavelength range 0.3–5 μm.
astro-ph.GA
0004-6361
Bisigello, L.
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Massimo, M.
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Charlot, S.
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Auricchio, N.
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Baldi, M.
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Bender, R.
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Bonino, D.
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Branchini, E.
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Brau-Nogue, S.
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Brescia, M.
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Camera, S.
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Capobianco, V.
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Carbone, C.
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Carretero, J.
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Casas, S.
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Euclid Collaboration
et al.
Bisigello, L.
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Massimo, M.
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Tortora, C.
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Allevato, V.
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Bolzonella, M.
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Gruppioni, C.
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Rodighiero, G.
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Serjeant, S.
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Gabarra, L.
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Feltre, A.
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Humphrey, A.
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Franca, F. La
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Landt, H.
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Mannucci, F.
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Prandoni, I.
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Stern, D.
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Spinoglio, L.
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Vergani, D.
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Vignali, C.
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Zamorani, G.
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Auricchio, N.
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Baldi, M.
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Bender, R.
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Bonino, D.
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Branchini, E.
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Brau-Nogue, S.
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Brescia, M.
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Camera, S.
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Capobianco, V.
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Carbone, C.
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Carretero, J.
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Casas, S.
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Castander, F.J.
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Castellano, M.
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Cavuoti, S.
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Bisigello, L., Massimo, M. and Tortora, C. , Euclid Collaboration and et al. (2024) Euclid preparation. XLIX. Selecting active galactic nuclei using observed colours. Astronomy & Astrophysics, 691, [A1]. (doi:10.1051/0004-6361/202450446).

Record type: Article

Abstract

The Euclid space mission will cover over 14 000 deg2 with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution in general, and AGN in particular. For this work we identified the best colour selection criteria for AGN, based only on Euclid photometry or including ancillary photometric observations, such as the data that will be available with the Rubin Legacy Survey of Space and Time (LSST) and observations already available from Spitzer/IRAC. The analysis was performed for unobscured AGN, obscured AGN, and composite (AGN and star-forming) objects. We made use of the spectro-photometric realisations of infrared-selected targets at all-z (SPRITZ) to create mock catalogues mimicking both the Euclid Wide Survey (EWS) and the Euclid Deep Survey (EDS). Using these mock catalogues, we estimated the best colour selection, maximising the harmonic mean (F1) of: (a) completeness, that is, the fraction of AGN correctly selected with respect to the total AGN sample; and (b) purity, that is, the fraction of AGN inside the selection with respect to the selected sample. The selection of unobscured AGN in both Euclid surveys (Wide and Deep) is possible with Euclid photometry alone with F1 = 0.22–0.23 (Wide and Deep), which can increase to F1 = 0.43–0.38 (Wide and Deep) if we limit out study to objects at z > 0.7. Such a selection is improved once the Rubin/LSST filters, that is, a combination of the u, g, r, or z filters, are considered, reaching an F1 score of 0.84 and 0.86 for the EDS and EWS, respectively. The combination of a Euclid colour with the [3.6]−[4.5] colour, which is possible only in the EDS, results in an F1 score of 0.59, improving the results using only Euclid filters, but worse than the selection combining Euclid and LSST colours. The selection of composite (fAGN = 0.05–0.65 at 8–40 μm) and obscured AGN is challenging, with F1 ≤ 0.3 even when including Rubin/LSST or IRAC filters. This is unsurprising since it is driven by the similarities between the broad-band spectral energy distribution of these AGN and star-forming galaxies in the wavelength range 0.3–5 μm.

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Accepted/In Press date: 8 August 2024
e-pub ahead of print date: 25 October 2024
Keywords: astro-ph.GA

Identifiers

Local EPrints ID: 496480
URI: http://eprints.soton.ac.uk/id/eprint/496480
ISSN: 0004-6361
PURE UUID: 6e75b061-6dc0-40ae-bb6d-f9b8a5127e4b

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Date deposited: 16 Dec 2024 17:51
Last modified: 16 Dec 2024 17:53

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Contributors

Author: L. Bisigello
Author: M. Massimo
Author: C. Tortora
Author: S. Fotopoulou
Author: V. Allevato
Author: M. Bolzonella
Author: C. Gruppioni
Author: L. Pozzetti
Author: G. Rodighiero
Author: S. Serjeant
Author: P.A.C. Cunha
Author: L. Gabarra
Author: A. Feltre
Author: A. Humphrey
Author: F. La Franca
Author: H. Landt
Author: F. Mannucci
Author: I. Prandoni
Author: M. Radovich
Author: F. Ricci
Author: M. Salvato
Author: F. Shankar
Author: D. Stern
Author: L. Spinoglio
Author: D. Vergani
Author: C. Vignali
Author: G. Zamorani
Author: L.Y.A. Yung
Author: S. Charlot
Author: N. Aghanim
Author: A. Amara
Author: S. Andreon
Author: N. Auricchio
Author: M. Baldi
Author: S. Bardelli
Author: P. Battaglia
Author: R. Bender
Author: D. Bonino
Author: E. Branchini
Author: S. Brau-Nogue
Author: M. Brescia
Author: S. Camera
Author: V. Capobianco
Author: C. Carbone
Author: J. Carretero
Author: S. Casas
Author: F.J. Castander
Author: M. Castellano
Author: S. Cavuoti
Corporate Author: Euclid Collaboration
Corporate Author: et al.

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