Euclid

Abstract:

The analysis of weak gravitational lensing in wide-field imaging surveys is considered to be a major cosmological probe of dark energy. Our capacity to constrain the dark energy equation of state relies on an accurate knowledge of the galaxy mean redshift ⟨z⟩. We investigate the possibility of measuring ⟨z⟩ with an accuracy better than 0.002 (1 + z) in ten tomographic bins spanning the redshift interval 0.2 < z < 2.2, the requirements for the cosmic shear analysis of Euclid. We implement a sufficiently realistic simulation in order to understand the advantages and complementarity, as well as the shortcomings, of two standard approaches: the direct calibration of ⟨z⟩ with a dedicated spectroscopic sample and the combination of the photometric redshift probability distribution functions (zPDFs) of individual galaxies. We base our study on the Horizon-AGN hydrodynamical simulation, which we analyse with a standard galaxy spectral energy distribution template-fitting code. Such a procedure produces photometric redshifts with realistic biases, precisions, and failure rates. We find that the current Euclid design for direct calibration is sufficiently robust to reach the requirement on the mean redshift, provided that the purity level of the spectroscopic sample is maintained at an extremely high level of > 99.8%. The zPDF approach can also be successful if the zPDF is de-biased using a spectroscopic training sample. This approach requires deep imaging data but is weakly sensitive to spectroscopic redshift failures in the training sample. We improve the de-biasing method and confirm our finding by applying it to real-world weak-lensing datasets (COSMOS and KiDS+VIKING-450).

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.