Euclid Quick Data Release (Q1): Euclid spectroscopy of QSOs. 1. Identification and redshift determination of 3500 bright QSOs

TL;DR

This paper demonstrates the viability of Euclid's slitless spectroscopy (NISP) to construct a large, high-purity bright quasar sample by cross-matching Gaia and AllWISE candidates and confirming redshifts with template-based cross-correlation and visual inspection. It delivers the first Euclid rest-frame NUV–NIR composite quasar spectrum free of telluric lines, quantifies spectral depth ($J_E \lesssim 21.5$, $H_E \lesssim 21.3$), and analyzes host–nucleus morphologies across redshift with a deep PSF-based compactness measure. The study shows that combining space-based spectroscopy with multi-wavelength pre-selection enhances quasar discovery and paves the way for more complete AGN catalogs in future Euclid data releases, including red quasar populations and improved selection strategies. These results enable robust quasar clustering and cross-correlation studies with galaxy and weak-lensing maps, advancing our understanding of AGN demographics and their role in cosmic structure formation.

Abstract

The slitless spectroscopy mode of the NISP onboard Euclid has enabled efficient spectroscopy of objects within a large FoV. We present a large and homogeneous sample of bright quasars identified from the Euclid Quick Data Release (Q1) by combining high-purity candidate selections from Gaia and WISE with the NISP spectra. Through visual inspection of the Euclid spectra of these quasar candidates, we identify approximately 3500 quasars with reliable redshifts at $0<z\lesssim 4.8$. We generate the first Euclid composite spectrum of quasars covering rest-frame NUV to NIR wavelengths without telluric lines, which will be pivotal to NIR quasar spectral analysis. We obtain an empirical spectroscopic depth of $J_{\rm E}\lesssim 21.5$ and $H_{\rm E}\lesssim 21.3$ at the sensitivity of the Wide Field Survey, beyond which the number of securely identified quasars declines sharply. We analyse VIS morphologies using Sersic and CAS metrics, and a deep-learning PSF fraction to track nuclear dominance. At low redshift ($z<0.5$), obvious host structures are common and a single Sersic model fits about half of the sources; at intermediate redshift ($0.5<z<2$), the nuclear component dominates, with 90% of the Sersic fits saturating at the upper index limit. In this intermediate redshift regime, $f_{\rm PSF}$ is available, and we use it as a more reliable compactness measure than the single-Sersic and CAS parameters to quantify nuclear versus host emission. We also explore the novel Euclid NIR colour space and discuss the role of these quasars in refining AGN selection techniques for future Euclid data releases. Our results highlight the potential of Euclid spectroscopy to advance quasar surveys and enable the construction of more complete AGN catalogues. The spectroscopic bright quasar catalogue of this work, and the composite quasar spectrum, will be available at https://cdsarc.cds.unistra.fr/. (abridged)

Figures (15)

• Figure 1: Example spectra of the visually identified quasars in the rest frame. The four columns from left to right show prominent emission lines used for the visual inspection in descending order of redshift: Mgii in the first column; H $\beta$, [Oiii], and H $\gamma$ in the second column; H $\alpha$ in the third column; and Hei + Pa $\gamma$, Pa $\beta$, Pa $\delta$, and [Siii] in the last column.
• Figure 2: Concentration parameter $\mu_{\mathrm{max}}-\mathrm{mag}$ as a function of the visual redshift $z_\mathrm{vi}$. The rejected region is shaded in pink, and is defined with $\mu_{\mathrm{max}}-\mathrm{mag}\xspace > -2$ at $z_{\mathrm{vi}} > 2$, as indicated by the red dashed lines. Sources inside the rejected region are considered to have spurious redshifts and are marked with black crosses.
• Figure 3: Redshift-magnitude distributions for the visually identified quasar sample using Q1 data. Top: two-dimensional distribution of versus $z_{\mathrm{vi}}$. Gaia-detected sources are shown as blue open squares, and sources not in Gaia DR3 are shown as orange circles. Blue contours trace the density of the Gaia subset, and red contours trace the density of the non-Gaia subset. The marginal histograms for $z_{\mathrm{vi}}$ (above) and (right) show the full sample (black steps), the Gaia subset (blue steps), and the non-Gaia subset (orange steps). Bottom: one-dimensional histograms of , , and for the same three samples. All histograms are normalised to unit area.
• Figure 4: Left: Distribution of the median spectral S/N within [12 047, 18 734] Å for visually identified quasars. The red dashed line at $\mathrm{S/N} = 2$ marks an empirical threshold below which the number of successful identifications declines rapidly. Middle and Right: Median S/N versus and magnitudes, respectively. Blue points show individual quasars, and the black lines indicate linear fits to $\log_{10}(\mathrm{S/N})$, with the fitted relations annotated. The red dashed line again marks $\mathrm{S/N} = 2$, and its intersection with the fit defines empirical limiting magnitudes of $\JE \approx 21.5$ and $\HE \approx 21.3$, shown by green dashed lines. These values represent practical limits for reliable spectral identification of quasars in Q1.
• Figure 5: $W1-W2$ versus $W2-W3$ colour-colour diagram of spectroscopically identified quasars in this work, where Gaia-detected sources are shown as blue open squares, and sources not in Gaia DR3 are shown as orange circles. The density distribution of the full identified quasar sample is indicated with green contour lines. point-like sources are shown as grey triangles. To ensure the reliability of the colours, only sources with adequate snr ($\texttt{w1snr}>5$, $\texttt{w2snr}>5$, and $\texttt{w3snr}>3$) are shown.