We provide predictions of the yield of 7 < z < 9 quasars from the Euclid wide survey, updating the calculation presented in the Euclid Red Book in several ways. We account for revisions to the Euclid near-infrared filter wavelengths; we adopt steeper rates of decline of the quasar luminosity function (QLF; φ) with redshift, φâ 10k(z - 6), k = -0.72, and a further steeper rate of decline, k = -0.92; we use better models of the contaminating populations (MLT dwarfs and compact early-type galaxies); and we make use of an improved Bayesian selection method, compared to the colour cuts used for the Red Book calculation, allowing the identification of fainter quasars, down to JAB ∼ 23. Quasars at z > 8 may be selected from Euclid OYJH photometry alone, but selection over the redshift interval 7 < z < 8 is greatly improved by the addition of z-band data from, e.g., Pan-STARRS and LSST. We calculate predicted quasar yields for the assumed values of the rate of decline of the QLF beyond z = 6. If the decline of the QLF accelerates beyond z = 6, with k = -0.92, Euclid should nevertheless find over 100 quasars with 7.0 < z < 7.5, and ∼25 quasars beyond the current record of z = 7.5, including ∼8 beyond z = 8.0. The first Euclid quasars at z > 7.5 should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, 7 < z < 8, M1450 < -25, using 8 m class telescopes to confirm candidates, but follow-up with JWST or E-ELT will be required to measure the faint-end slope. Contamination of the candidate lists is predicted to be modest even at JAB ∼ 23. The precision with which k can be determined over 7 < z < 8 depends on the value of k, but assuming k = -0.72 it can be measured to a 1σ uncertainty of 0.07.

Euclid preparation: V. Predicted yield of redshift 7 < z < 9 quasars from the wide survey

Auricchio N.
Membro del Collaboration Group
;
Baldi M.
Membro del Collaboration Group
;
Cimatti A.
Membro del Collaboration Group
;
Marulli F.
Membro del Collaboration Group
;
Mauri N.
Membro del Collaboration Group
;
Metcalf R. B.
Membro del Collaboration Group
;
Moresco M.;Moscardini L.
Membro del Collaboration Group
;
Tenti M.
Membro del Collaboration Group
;
2019

Abstract

We provide predictions of the yield of 7 < z < 9 quasars from the Euclid wide survey, updating the calculation presented in the Euclid Red Book in several ways. We account for revisions to the Euclid near-infrared filter wavelengths; we adopt steeper rates of decline of the quasar luminosity function (QLF; φ) with redshift, φâ 10k(z - 6), k = -0.72, and a further steeper rate of decline, k = -0.92; we use better models of the contaminating populations (MLT dwarfs and compact early-type galaxies); and we make use of an improved Bayesian selection method, compared to the colour cuts used for the Red Book calculation, allowing the identification of fainter quasars, down to JAB ∼ 23. Quasars at z > 8 may be selected from Euclid OYJH photometry alone, but selection over the redshift interval 7 < z < 8 is greatly improved by the addition of z-band data from, e.g., Pan-STARRS and LSST. We calculate predicted quasar yields for the assumed values of the rate of decline of the QLF beyond z = 6. If the decline of the QLF accelerates beyond z = 6, with k = -0.92, Euclid should nevertheless find over 100 quasars with 7.0 < z < 7.5, and ∼25 quasars beyond the current record of z = 7.5, including ∼8 beyond z = 8.0. The first Euclid quasars at z > 7.5 should be found in the DR1 data release, expected in 2024. It will be possible to determine the bright-end slope of the QLF, 7 < z < 8, M1450 < -25, using 8 m class telescopes to confirm candidates, but follow-up with JWST or E-ELT will be required to measure the faint-end slope. Contamination of the candidate lists is predicted to be modest even at JAB ∼ 23. The precision with which k can be determined over 7 < z < 8 depends on the value of k, but assuming k = -0.72 it can be measured to a 1σ uncertainty of 0.07.
Barnett R.; Warren S.J.; Mortlock D.J.; Cuby J.-G.; Conselice C.; Hewett P.C.; Willott C.J.; Auricchio N.; Balaguera-Antolinez A.; Baldi M.; Bardelli S.; Bellagamba F.; Bender R.; Biviano A.; Bonino D.; Bozzo E.; Branchini E.; Brescia M.; Brinchmann J.; Burigana C.; Camera S.; Capobianco V.; Carbone C.; Carretero J.; Carvalho C.S.; Castander F.J.; Castellano M.; Cavuoti S.; Cimatti A.; Cledassou R.; Congedo G.; Conversi L.; Copin Y.; Corcione L.; Coupon J.; Courtois H.M.; Cropper M.; Da Silva A.; Duncan C.A.J.; Dusini S.; Ealet A.; Farrens S.; Fosalba P.; Fotopoulou S.; Fourmanoit N.; Frailis M.; Fumana M.; Galeotta S.; Garilli B.; Gillard W.; Gillis B.R.; Gracia-Carpio J.; Grupp F.; Hoekstra H.; Hormuth F.; Israel H.; Jahnke K.; Kermiche S.; Kilbinger M.; Kirkpatrick C.C.; Kitching T.; Kohley R.; Kubik B.; Kunz M.; Kurki-Suonio H.; Laureijs R.; Ligori S.; Lilje P.B.; Lloro I.; Maiorano E.; Mansutti O.; Marggraf O.; Martinet N.; Marulli F.; Massey R.; Mauri N.; Medinaceli E.; Mei S.; Mellier Y.; Metcalf R.B.; Metge J.J.; Meylan G.; Moresco M.; Moscardini L.; Munari E.; Neissner C.; Niemi S.M.; Nutma T.; Padilla C.; Paltani S.; Pasian F.; Paykari P.; Percival W.J.; Pettorino V.; Polenta G.; Poncet M.; Pozzetti L.; Raison F.; Renzi A.; Rhodes J.; Rix H.-W.; Romelli E.; Roncarelli M.; Rossetti E.; Saglia R.; Sapone D.; Scaramella R.; Schneider P.; Scottez V.; Secroun A.; Serrano S.; Sirri G.; Stanco L.; Sureau F.; Tallada-Crespi P.; Tavagnacco D.; Taylor A.N.; Tenti M.; Tereno I.; Toledo-Moreo R.; Torradeflot F.; Valenziano L.; Vassallo T.; Wang Y.; Zacchei A.; Zamorani G.; Zoubian J.; Zucca E.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/712158
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