Cosmology

Abstract:

In this paper, we investigate the relationship between 150 MHz luminosity and the star-formation rate – the SFR-L150 MHz relation – using 150 MHz measurements for a near-infrared selected sample of 118 517 z < 1 galaxies. New radio survey data offer compelling advantages over previous generation surveys for studying star formation in galaxies, including huge increases in sensitivity, survey speed, and resolution, while remaining impervious to extinction. The LOFAR Surveys Key Science Project is transforming our understanding of the low-frequency radio sky, with the 150 MHz data over the European Large Area Infrared Space Observatory Survey-North 1 field reaching an rms sensitivity of 20 μJy beam−1 over 10 deg2 at 6 arcsec resolution. All of the galaxies studied have SFR and stellar mass estimates that were derived from energy balance spectral energy distribution fitting using redshifts and aperture-matched forced photometry from the LOFAR Two-metre Sky Survey (LoTSS) Deep Fields data release. The impact of active galactic nuclei (AGN) is minimised by leveraging the deep ancillary data in the LoTSS data release, alongside median-likelihood methods that we demonstrate are resistant to AGN contamination. We find a linear and non-evolving SFR-L150 MHz relation, apparently consistent with expectations based on calorimetric arguments, down to the lowest SFRs < 0.01M⊙ yr−1. However, we also recover compelling evidence for stellar mass dependence in line with previous work on this topic, in the sense that higher mass galaxies have a larger 150 MHz luminosity at a given SFR, suggesting that the overall agreement with calorimetric arguments may be a coincidence. We conclude that, in the absence of AGN, 150 MHz observations can be used to measure accurate galaxy SFRs out to z = 1 at least, but it is necessary to account for stellar mass in the estimation in order to obtain 150 MHz-derived SFRs accurate to better than 0.5 dex. Our best-fit relation is log10(L150 MHz ∕W Hz−1) = (0.90 ± 0.01)log10(ψ∕M⊙ yr−1) + (0.33 ± 0.04)log10(M∕1010M⊙) + 22.22 ± 0.02.

Abstract:

In recent years, the level of the extragalactic radio background has become a point of considerable interest, with some lines of argument pointing to an entirely new cosmological synchrotron background. The contribution of the known discrete source population to the sky temperature is key to this discussion. Because of the steep spectral index of the excess over the cosmic microwave background, it is best studied at low frequencies where the signal is strongest. The Low-Frequency Array (LOFAR) wide and deep sky surveys give us the best constraints yet on the contribution of discrete extragalactic sources at 144 MHz, and in particular allow us to include contributions from diffuse, low-surface-brightness emission that could not be fully accounted for in previous work. We show that, even with these new data, known sources can still only account for around a quarter of the estimated extragalactic sky temperature at LOFAR frequencies.

Abstract:

VANDELS is an ESO Public Spectroscopic Survey designed to build a sample of high-signal-to-noise ratio, medium-resolution spectra of galaxies at redshifts between 1 and 6.5. Here we present the final Public Data Release of the VANDELS Survey, comprising 2087 redshift measurements. We provide a detailed description of sample selection, observations, and data reduction procedures. The final catalogue reaches a target selection completeness of 40% at iAB = 25. The high signal-to-noise ratio of the spectra (above 7 in 80% of the spectra) and the dispersion of 2.5 Å allowed us to measure redshifts with high precision, the redshift measurement success rate reaching almost 100%. Together with the redshift catalogue and the reduced spectra, we also provide optical mid-infrared photometry and physical parameters derived through fitting the spectral energy distribution. The observed galaxy sample comprises both passive and star forming galaxies covering a stellar mass range of 8.3 < Log(M∗/M⊙) < 11.7.

Abstract:

Over the past decade, several works have used the ratio between total (rest 8−1000 μm) infrared and radio (rest 1.4 GHz) luminosity in star-forming galaxies (qIR), often referred to as the infrared-radio correlation (IRRC), to calibrate the radio emission as a star formation rate (SFR) indicator. Previous studies constrained the evolution of qIR with redshift, finding a mild but significant decline that is yet to be understood. Here, for the first time, we calibrate qIR as a function of both stellar mass (M⋆) and redshift, starting from an M⋆-selected sample of > 400 000 star-forming galaxies in the COSMOS field, identified via (NUV − r)/(r − J) colours, at redshifts of 0.1 < z < 4.5. Within each (M⋆,z) bin, we stacked the deepest available infrared/sub-mm and radio images. We fit the stacked IR spectral energy distributions with typical star-forming galaxy and IR-AGN templates. We then carefully removed the radio AGN candidates via a recursive approach. We find that the IRRC evolves primarily with M⋆, with more massive galaxies displaying a systematically lower qIR. A secondary, weaker dependence on redshift is also observed. The best-fit analytical expression is the following: qIR(M⋆, z) = (2.646 ± 0.024) × (1 + z)( − 0.023 ± 0.008)–(0.148 ± 0.013) × (log M⋆/M⊙ − 10). Adding the UV dust-uncorrected contribution to the IR as a proxy for the total SFR would further steepen the qIR dependence on M⋆. We interpret the apparent redshift decline reported in previous works as due to low-M⋆ galaxies being progressively under-represented at high redshift, as a consequence of binning only in redshift and using either infrared or radio-detected samples. The lower IR/radio ratios seen in more massive galaxies are well described by their higher observed SFR surface densities. Our findings highlight the fact that using radio-synchrotron emission as a proxy for SFR requires novel M⋆-dependent recipes that will enable us to convert detections from future ultra-deep radio surveys into accurate SFR measurements down to low-M⋆ galaxies with low SFR.