Prof. David Alonso

Abstract:

Radio-AGNs (active galactic nuclei) are observed to be more strongly clustered than non-active galaxies, though it is unclear whether this is simply due to their preference for massive host galaxies, or if they reside in distinct environments beyond this mass dependence. Using data from three fields covered by the MIGHTEE survey, we measure the angular two-point cross-correlation functions with a large, stellar mass-limited population of near-infrared selected galaxies, overcoming limitations of previous single-deep-field studies. By fitting halo occupation distribution models, we infer the galaxy bias parameters, b, for radio-AGN in three redshift ranges with median redshifts of , , and , finding , , and , respectively. The typical dark matter halo mass decreases with increasing redshift: , , and , which we attribute to the increased abundance of cold gas required to fuel AGN activity at earlier times. The AGN duty cycle is determined to be per cent, and we estimate that the total energy radiated by radio-jets over is per halo, which is sufficient to account for the observed excess heating of gas beyond that of gravitational collapse. Comparing the typical dark matter halo masses to the values obtained for the control sample, we find that the halo masses of radio-AGN are , , and times greater than those of the stellar mass- and redshift-matched galaxies. This difference could arise because AGN feedback suppresses stellar mass growth while leaving halo mass unchanged, or because radio-AGN preferentially reside in earlier forming haloes which are more strongly clustered.

Abstract:

Recent work has developed a formalism for computing angular power spectra directly from catalogues containing field values at discrete positions on the sky, thereby circumventing the need to create pixelized maps of the fields, as well as avoiding aliasing and finite-resolution effects. We adapt this formalism to incorporate template deprojection for mitigating systematic biases in the measured angular power spectra. We also introduce an alternative method of mitigating the ‘deprojection bias’ – the loss of modes induced by deprojection – employing simple simulations to compute a transfer function. We find that this approach performs at least as well as existing methods, and is relatively insensitive to how well one can guess the true power spectrum of the observed field, except at the largest scales (). Additionally, we develop exact expressions for the bias introduced by deprojection in the shot-noise component, which further improves the accuracy of this approach. We test our formalism on simulated data sets, demonstrating its applicability both to discretely sampled fields, and to the special case of galaxy clustering, with the survey selection function defined in terms of a random catalogue or as a continuous sky map. After removing the bias in the shot noise and correcting for the remaining mode loss using a transfer function, our formalism produces unbiased measurements of the angular power spectrum in all scenarios tested here. Finally, we apply our formalism to real data and show it produces results consistent with the standard map-based pseudo- formalism. We implement our method in the public code NaMaster.

Abstract:

We analyse the large-scale angular clustering of quasars in the Gaia-unWISE quasar catalog, Quaia, and their cross-correlation with maps of the lensing convergence of the Cosmic Microwave Background (CMB), to constrain the level of primordial non-Gaussianity (PNG). Specifically, we target the scale-dependent bias that would be induced by PNG on biased tracers of the matter inhomogeneities on large scales. The Quaia sample is particularly well suited for this analysis, given the large effective volume covered, and our ability to map out the main potential sources of systematic contamination and mitigate their impact. Using the universality relation to characterise the response of the quasar overdensity to PNG (pϕ = 1), we report constraints on the local-type PNG parameter f NL of f NL = -20.5+19.0 -18.1 (68% C.L.) by combining the quasar auto-correlation and its cross-correlation with CMB lensing in two tomographic redshift bins (or f NL = -28.7+26.1 -24.6 if assuming a lower response for quasars, pϕ = 1.6). The error on f NL can be further improved if the cross-correlation between the tomographic redshift bins is included. Using the CMB lensing cross-correlations alone, we find fNL = -13.8+26.7 -25.0 and fNL = -15.6+42.3 -34.8 for pϕ = 1 and pϕ = 1.6 respectively. These are the tightest constraints on fNL to date from angular clustering statistics and cross-correlations with CMB lensing.