Euclid

Abstract:

Type Ia supernova (SN Ia) standardisation parameters exhibit evidence for systematic variation across the host galaxy star-formation rate–stellar mass (SFR−M⋆) plane, motivating the incorporation of galaxy SFR information in cosmological inference. SFRs are commonly estimated via spectral energy distribution (SED) fitting with far-infrared (FIR) measurements to account for dust-obscured star formation. Such FIR coverage will, however, be limited for upcoming time-domain surveys such as the Rubin Observatory Legacy Survey of Space and Time (LSST), necessitating the use of alternative SFR tracers. Here, we reconstruct the SFR–M⋆ plane using 1.4 GHz diagnostics, to test the consistency of host classifications against FIR-constrained SED-based estimates. Within this plane, SN Ia host galaxies are divided into three regions: Region 1 (low-mass), Region 2 (high-mass star-forming) and Region 3 (high-mass passive). We find that ∼84 per cent of SN hosts retain identical region assignments when using radio versus FIR-constrained SED-derived SFRs. Measuring SN Ia nuisance parameters (α, β, M) within each subregion, we find consistent values between the two SFR–M⋆ plane reconstructions, indicating limited sensitivity to SFR estimator choice, with the largest deviations in Region 3 at ∼1.1σ. Across the three 1.4 GHz SFR–M⋆ subregions, we confirm the region-dependent variation in SN Ia standardisation parameters–particularly β–reported in our earlier SED-based analysis. With near-complete radio coverage of the LSST footprint anticipated from current and forthcoming radio continuum surveys (e.g., Square Kilometre Array), radio SFR calibrations will become an increasingly useful and scalable approach to host galaxy classification, supporting the construction of robust SN Ia subsamples for precision cosmology.

Abstract:

We present a JWST analysis of intracluster light (ICL) in XLSSC 122 at z = 1.98, currently the most distant known strong-lensing galaxy cluster with an evolved member population. Using deep JWST imaging complemented by Hubble Space Telescope data and careful control of systematics, we robustly detect diffuse emission extending to several hundred kiloparsecs from the brightest cluster galaxy (BCG) down to ∼29magarcsec−2 . Multicomponent point-spread-function-convolved Sérsic modeling separates the surface brightness profiles into three components: a BCG core, a BCG envelope, and an ICL component, with stable Sérsic indices across wavelengths. Nearly flat color profiles indicate minimal radial variation in the stellar populations of the BCG envelope and the ICL. The median ICL fraction measured across seven bands is ∼17%, demonstrating that the buildup of intracluster stars in massive halos was already well underway by z ∼ 2. The ICL fraction peaks near 5000 Å in the rest frame, which provides the first confirmation at z > 1 that this characteristic rise is a feature of dynamically active clusters. We also detect a southern excess of ICL relative to the best-fit Sérsic model and quantify it using wavelet-based modeling, providing additional support that this system is dynamically active. The BCG + ICL light distribution and strong-lensing mass map show strong morphological agreement within ∼100 kpc. These findings establish the ICL as an early forming and dynamically informative component of massive halos.

Abstract:

The upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will enable astronomers to discover rare and distant astrophysical transients. Host-galaxy association is crucial for selecting the most scientifically interesting transients for follow-up. LSST deep drilling field (DDF) observations will detect distant transients occurring in galaxies below the detection limits of most all-sky catalogs. Here, we investigate the use of preexisting, field-specific catalogs for host identification in the DDFs and a ranking of their usefulness. We have compiled a database of 70 deep catalogs that overlap with the Rubin DDFs and constructed thin catalogs to be homogenized and combined for transient-host matching. A systematic ranking of their utility is discussed and applied based on the inclusion of information such as spectroscopic redshifts and morphological information. Utilizing this data against a Dark Energy Survey sample of supernovae with pre-identified hosts in the XMM-Large Scale Structure and the Extended Chandra Deep Field-South fields, we evaluate different methods for transient-host association in terms of both accuracy and processing speed. We also apply light data-cleaning techniques to identify and remove contaminants within our associations, such as diffraction spikes and blended galaxies where the correct host cannot be determined with confidence. We use a lightweight machine learning approach in the form of extreme gradient boosting to generate confidence scores in our contaminant selections and associated metrics. Finally, we discuss the computational expense of implementation within the LSST transient alert brokers, which will require efficient, fast-paced processing to handle the large stream of survey data.

Abstract:

Abstract A key question in extragalactic astronomy is how the star-formation rate density (SFRD) evolves over cosmic time. A powerful way of addressing this question is using radio-continuum observations, where the radio waves are unaffected by dust and are able to reach sufficient resolution to resolve individual galaxies. We present an investigation of the 1.4 GHz radio luminosity functions (RLFs) of star-forming galaxies (SFGs) and Active Galactic Nuclei (AGN) using deep radio continuum observations in the COSMOS and XMM–LSS fields, covering a combined area of ∼4 deg2. These data enable the most accurate measurement of the evolution in the SFRD from mid-frequency radio continuum observations. We model the total RLF as the sum of evolving SFG and AGN components, negating the need for individual source classification. We find that the SFGs have systematically higher space densities at fixed luminosity than found in previous radio studies, but consistent with more recent studies with MeerKAT. We attribute this to the excellent low-surface brightness sensitivity of MeerKAT. We then determine the evolution of the SFRD. Adopting the far-infrared – radio correlation results in a significantly higher SFRD at z > 1, compared to combined UV and far-infrared measurements. However, using more recent relations for the correlation between star-formation rate and radio luminosity, based on full spectral energy distribution modelling, can resolve this apparent discrepancy. Thus radio observations provide a powerful method of determining the total SFRD, in the absence of dust-sensitive far-infrared data.

Abstract:

We present a quadratic estimator that detects and reconstructs spatially varying multiplicative (m-) bias in weak lensing shear measurements, by exploiting the mode coupling that it generates. The method combines E and B modes with inverse-variance weights, to yield an unbiased reconstruction of to first order. We study the ability of future Stage IV surveys to obtain an unbiased reconstruction of the m-bias in differing scenarios, considering differing bias morphologies, and characteristic scales, as well as differing metrics to quantify the signal-to-noise ratio of the reconstructed map. We consider an m pattern repeating on sky patches, as might be the case for an m field caused by focal-plane systematics. With a Euclid-like redshift distribution, we find that root mean square (rms) variations in m-bias may be detected at the 20 level, after stacking between and patches (rising to between and for 1 per cent rms variations, data volumes that are becoming available with upcoming surveys), depending on the morphology of the m pattern. We show that these results are robust against the cosmological model assumed in the reconstruction, as well as the presence of intrinsic alignments or baryonic effects, and that the method shows no spurious response to additive (c-) bias. These results demonstrate that percent-level, spatially varying m-bias can be detected at high significance, enabling diagnosis and mitigation in the Stage IV weak lensing era.