Euclid

Abstract:

Abstract Determining the relationship between star-formation rate (SFR) and the radio luminosity (L1.4) is critical if we are to trace the star-formation history of the Universe dust-agnostically using current and future radio facilities. However, until now, such work has relied on potentially biased binary classifications of sources to remove contaminating active galactic nuclei (AGN). We present a new, statistically-driven methodology for deriving the SFR – L1.4 relation, removing the need for problematic cuts. We use a Bayesian hierarchical mixture model fit to the radio-detected sources in the deep MIGHTEE COSMOS DR1 catalogue, incorporating the full SFR posterior probability distributions generated by state-of-the-art spectral energy distribution fitting code GRAHSP. This allows us to probabilistically determine a mean SFR – L1.4 relation for the SF dominated galaxies, whilst accounting for changing fractions of SF dominated sources across redshift, radio luminosity and stellar mass ranges. We find that the SFR – radio luminosity correlation exhibits a significant dependence on redshift, but a stellar mass dependence that is weaker than previous studies. Our resultant SFR-radio correlation is log10(SFR/M⊙ yr−1) = 0.790 × (log10(L1.4/W Hz−1) − 23) + 1.244 × (1 + z)0.122 − 0.033 × (log10(M*/M⊙) − 10), with an intrinsic scatter of 0.178 dex. We show that this redshift evolution could be explained by a moderate evolution in the radio spectral index of SF galaxies. We attribute the lack of observed strong dependence on stellar mass, compared to recent studies, to the novel statistical approach that does not rely on cuts to remove AGN.

Abstract:

Abstract Cosmic filaments have been recognised as influencing galaxy evolution, but their connection to galactic cold gas reservoirs is elusive, particularly at low redshifts. We investigate the influence of filaments on neutral hydrogen (H i) detections in galaxies at 0.02 < z < 0.09, using the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) survey in the COSMOS and XMM-LSS fields. We measure the fraction of optical galaxies from the Dark Energy Spectroscopic Instrument (DESI) Survey detected in H i emission as a function of stellar mass, morphology, local density, and the distance to the nearest filament. We find that galaxies closer to filaments have higher stellar masses, higher local densities, and a larger early-type fraction, all of which affect the H i detection. After controlling for these dependencies, filaments have measurable effects on H i detection. Late-type galaxies in low-local density environments show reduced H i detection fractions close to filaments across all stellar mass ranges, suggesting potential gas depletion through ram pressure stripping and cosmic web detachment. Massive early-type galaxies show an enhanced H i detection fraction in filaments compared to the voids, suggesting possible gas replenishment through filamentary accretion or gas-rich mergers. Our results suggest that cosmic filaments influence galactic H i gas reservoirs through various competing processes, whose relative importance varies with stellar mass and local density.

Abstract:

Abstract Radio continuum surveys provide samples of active galactic nuclei (AGN) and star forming galaxies (SFGs) to high redshifts, free of biases due to dust obscuration. However, radio detected sources require multi-wavelength counterparts to understand their intrinsic properties (e.g. redshift, stellar mass) and to study the evolution of star formation and AGN activity. In this work we present host galaxy counterparts for the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) survey continuum Data Release 1 in regions with the best ancillary data (totalling 7.5 sq. deg). We combine statistical cross-matching and visual inspection to identify Ks-band selected host galaxies, and additionally combine multiple radio components into single physical objects, where needed. This results in a combined radio catalogue of ~66 000 sources, with host counterparts and redshifts identified for ~95 per cent of sources in the COSMOS field, ~91 per cent in XMM-LSS and ~90 per cent in CDFS-DEEP. This includes a significant fraction of sources with spectroscopic redshifts within the COSMOS field (~50 per cent), with ~30 and ~20 per cent in the XMM-LSS and CDFS-DEEP fields respectively. Using the cross-matched catalogue, we make an initial identification of radio-excess and star forming galaxies based on comparisons of the radio luminosities to host star formation rates. Using this split as a proxy for radio loud AGN or SFGs, we present expectations for the redshift distributions of these sources, finding broad agreement with those from deep radio luminosity functions and simulated catalogues.

Abstract:

A primary target of the Euclid space mission is to constrain early-universe physics by searching for deviations from a primordial Gaussian random field. A significant detection of primordial non-Gaussianity would rule out the simplest models of cosmic inflation and transform our understanding of the origin of the Universe. This paper forecasts how well field-level inference of galaxy redshift surveys can constrain the amplitude of local primordial non-Gaussianity, f NL^local, within a Bayesian hierarchical framework, in the upcoming Euclid data. We designed and simulated mock datasets and performed Markov chain Monte Carlo analyses using a full-field forward modelling approach. By including the formation history of the cosmic matter field in the analysis, the method takes into account all available probes of primordial non-Gaussianity, and goes beyond statistical summary estimators of f NL^local. Probes include, for example, two-point and higher-order statistics, peculiar velocity fields, and scale-dependent galaxy biases. Furthermore, the method simultaneously handles systematic survey effects, such as selection effects, survey geometries, and galaxy biases. The forecast shows that, using simulated Euclid data, the method can achieve a precision of σ(f NL^local) = 2.6 (68.3% confidence level), assuming a grid resolution of ΔL = 31.25 h ⁻¹ Mpc and a cut-off scale of k NF = 0.1 h Mpc⁻¹. We also provide data products, including realistic simulations with non-zero values of f NL^local and maps of adiabatic curvature fluctuations. The results underscore the feasibility and advantages of field-level inference to constrain f NL^local in galaxy redshift surveys. Our approach consistently captures all the information available in the large-scale structure to constrain f NL^local, and resolves the degeneracy between early-universe physics and late-time gravitational effects, while mitigating the impact of systematic and observational effects.