Hintze Centre for Astrophysical Surveys

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 Radio galaxies play a significant role in galaxy evolution through feedback mechanisms, making it important to characterize the environments in which they reside. We measure the cross-correlation between the positions of radio sources in the MIGHTEE survey with cosmic microwave background lensing measurements from the Atacama Cosmology Telescope over 20 deg2 to flux densities S1.4 GHz > 40 μJy, detecting the signal at ∼4σ significance. By combining this with auto-correlation measurements of low- and high-redshift radio samples, we constrain the redshift evolution of the galaxy bias parameter, b(z). Fitting different models for the redshift evolution of the bias, we find that both a model inversely proportional to the linear growth factor, $b(z)=(1.63^{+0.19}_{-0.22})/D(z)$, and a model where bias grows linearly with redshift, $b(z)=(0.49^{+0.44}_{-0.32})+(1.62^{+0.37}_{-0.51})z$, provide comparably good fits to the data, with the current measurements unable to distinguish between them. Using a radio luminosity function, we estimate the fraction of sources that are active galactic nuclei (AGNs) or star-forming galaxies (SFGs) as a function of redshift, and model the individual contributions of AGNs and SFGs to the total bias. This approach allows us to measure the bias of AGNs and SFGs without individual source classifications. Though no single model is favoured significantly, the best-fitting model gives $b_{\rm AGN}(z) = (2.60^{+0.65}_{-0.91})/D(z)$ compared to $b_{\rm SFG}(z) = (0.52^{+0.47}_{-0.34})/D(z)$. Incorporating SFG bias measurements from previous work as a prior tightens these constraints to $b_{\rm AGN}(z) = (1.96^{+0.37}_{-0.40})/D(z)$ and $b_{\rm SFG}(z) = (0.90^{+0.06}_{-0.06})/D(z)$.

Abstract:

Abstract Understanding how galaxies populate and grow within dark matter haloes is essential for linking the observed evolution of galaxies to the hierarchical growth of structure. We present a galaxy clustering analysis using optical and near-infrared data from the UltraVISTA and VIDEO surveys covering 9.3 deg2 across the COSMOS, XMM-LSS and ECDF-S fields, ∼5 × larger than previous comparable studies, providing sufficient volume to determine the halo occupation of the most massive galaxies to z ∼ 4. We measure the angular two-point correlation function for stellar-mass-selected galaxies over 0.25 < z < 4 and by combining the three fields, we reduce the cosmic variance by a factor of ∼2 compared to the individual fields. The stellar-to-halo mass ratio peaks at a halo mass of Mh ≈ 1012 M⊙ and is a maximum at z ∼ 1. For the most massive galaxies, the peak halo mass ($M_{h}^{\rm peak}$) increases from z = 1 → 0, while the peak stellar mass in such haloes remains approximately constant, indicating that at z < 1 massive galaxy formation becomes less efficient. We also find a steady increase in the satellite fraction since z ∼ 1, from which we infer that massive halos continue to grow hierarchically while their central galaxies experience suppressed stellar-mass growth. We suggest this is due to the central massive galaxies having their growth controlled by feedback from active galactic nuclei feedback, likely from low-power stochastic radio emission.

Abstract:

In the coming years, the Vera Rubin Observatory’s Legacy Survey of Space and Time (Rubin-LSST) and the Nancy Grace Roman Space Telescope’s (Roman) High Latitude Time Domain Survey (HLTDS) are expected to discover more than a million Type Ia supernovae (SNe Ia), several orders of magnitude more than current samples and with a tighter control on systematic uncertainties. One of the largest systematic uncertainties in cosmological analyses with SNe Ia is the accuracy of the spectrophotometric model for SNe Ia time series data, which depends on the photometric calibration of the surveys. To quantify the impact of this uncertainty, we analyze simulated Rubin-LSST and HLTDS data, perturb the photometric zero-points and filter mean wavelengths, and propagate these systematics to spectral model recovery, estimated distances, and dark energy Figure of Merit (FoM) based on the w0waCDM model. Zero-point shifts of 5 mmag and filter mean wavelength shifts of 5 Å lead to a ∼50% decrease in the FoM relative to a statistical-only case when calibration uncertainties are propagated only through light-curve fitting. The same calibration shifts applied only during model training produce a smaller ∼13% degradation. Contrary to previous analyses, calibration uncertainties in light-curve fitting dominate over those from model training. Their effect during light-curve fitting varies smoothly with redshift and is nearly degenerate with cosmology, preventing mitigation through self-calibration. Finally, we show that the FoM dependence on the size of the calibration uncertainties (in the range of expected sizes) is roughly linear.