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Abstract:

We present a comprehensive study of the physical origin of radio emission in optical quasars at redshifts z < 2.5. We focus particularly on the associations between compact radio emission, dust reddening, and outflows identified in our earlier work. Leveraging the deepest low-frequency radio data available to date (LoTSS Deep DR1), we achieve radio detection fractions of up to 94%, demonstrating the virtual ubiquity of radio emission in quasars, and a continuous distribution in radio loudness. Through our analysis of radio properties, combined with spectral energy distribution modelling of deep multiwavelength photometry, we establish that the primary source of radio emission in quasars is the active galactic nucleus (AGN), rather than star formation. Modelling the dust reddening of the accretion disc emission shows a continuous increase in radio detection in quasars as a function of the reddening parameter E(B − V), suggesting a causal link between radio emission and dust reddening. Confirming previous findings, we observe that the radio excess in red quasars is most pronounced for sources with compact radio morphologies and intermediate radio loudness. We find a significant increase in [O III] and C IV outflow velocities for red quasars not seen in our control sample, with particularly powerful [O III] winds in those around the threshold from radio-quiet to radio-loud. Based on the combined characterisation of radio, reddening, and outflow properties in our sample, we favour a model in which the compact radio emission observed in quasars originates in compact radio jets and their interaction with a dusty, circumnuclear environment. In particular, our results align with the theory that jet-induced winds and shocks resulting from this interaction are the origin of the enhanced radio emission in red quasars. Further investigation of this model is crucial for advancing our understanding of quasar feedback mechanisms and their role in galaxy evolution.

Abstract:

Context. The Euclid space satellite mission will measure the large-scale clustering of galaxies at an unprecedented precision, providing a unique probe of modifications to the ?CDM model. Aims. We investigated the approximations needed to efficiently predict the large-scale clustering of matter and dark matter halos in the context of modified gravity and exotic dark energy scenarios. We examined the normal branch of the Dvali-Gabadadze-Porrati model, the Hu-Sawicki f(R) model, a slowly evolving dark energy model, an interacting dark energy model, and massive neutrinos. For each, we tested approximations for the perturbative kernel calculations, including the omission of screening terms and the use of perturbative kernels based on the Einstein-de Sitter universe; we explored different infrared-resummation schemes, tracer bias models and a linear treatment of massive neutrinos; we investigated various approaches for dealing with redshift-space distortions and modelling the mildly nonlinear scales, namely the Taruya-Nishimishi-Saito prescription and the effective field theory of large-scale structure. This work provides a first validation of the various codes being considered by Euclid for the spectroscopic clustering probe in beyond-?CDM scenarios. Methods. We calculated and compared the χ2 statistic to assess the different modelling choices. This was done by fitting the spectroscopic clustering predictions to measurements from numerical simulations and perturbation theory-based mock data. We compared the behaviour of this statistic in the beyond-?CDM cases, as a function of the maximum scale included in the fit, to the baseline ?CDM case. Results. We find that the Einstein-de Sitter approximation without screening is surprisingly accurate for the modified gravity cases when comparing to the halo clustering monopole and quadrupole obtained from simulations and mock data. Further, we find the same goodness-of-fit for both cases - the one including and the one omitting non-standard physics in the predictions. Our results suggest that the inclusion of multiple redshift bins, higher-order multipoles, higher-order clustering statistics (such as the bispectrum), and photometric probes such as weak lensing, will be essential to extract information on massive neutrinos, modified gravity and dark energy. Additionally, we show that the three codes used in our analysis, namely, PBJ, Pybird and MG-Copter, exhibit sub-percent agreement for k ≤ 0.5 h Mpc-1 across all the models. This consistency underscores their value as reliable tools.