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Abstract:

Type Ia supernova (SN Ia) standardization parameters exhibit evidence for systematic variation across the host galaxy star formation rate–stellar mass (SFR) 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– 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 per cent of SN hosts retain identical region assignments when using radio versus FIR-constrained SED-derived SFRs. Measuring SN Ia nuisance parameters () within each subregion, we find consistent values between the two SFR– plane reconstructions, indicating limited sensitivity to SFR estimator choice, with the largest deviations in Region 3 at . Across the three 1.4 GHz SFR– subregions, we confirm the region-dependent variation in SN Ia standardization parameters – particularly – 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 an example cluster follow-up study with Euclid. Our target, a z ∼ 1.74 candidate cluster nicknamed the ‘Puddle’, was initially discovered by the Massive and Distant Clusters of WISE Survey 2 as a zphot ∼ 1.65 candidate cluster. It was also detected independently as a zphot ∼ 1.5 candidate with the two cluster-finding algorithms in Euclid Quick Release 1 (Q1). A Keck MOSFIRE spectrum shows the brightest nucleus is at z = 1.74 and is dominated by an active galactic nucleus. Our analysis focused on the galaxy population and the brightest cluster galaxy (BCG), and is based on Euclid and ancillary photometry. Compared to similar fields, we measured an overdensity of 110 ± 14 galaxies with HE ≤ 22.25 in a 2′ radius around the BCG. About 18 ± 4% of the completeness-corrected galaxy population is red, which is consistent with some clusters at z > 1.5 but lower than others. Euclid imaging revealed that six or seven galaxies appear to be assembling to form the future BCG. Spectral energy distribution fitting suggests that the merging BCG has a stellar mass of 5.7 ± 0.3 × 10¹¹â€†M⊙ and that it experienced a short burst of star formation ∼300 Myr ago. Its morphology and star-formation history suggest that the proto-BCG is a more evolved version of the merging core of SPT2349−56. These systems indicate that multiobject mergers might be a common BCG formation process. Assuming a similar density of mergers in the Euclid Wide Survey, we expect that Euclid will discover approximately 400 assembling BCGs by the end of its mission.

Abstract:

The Euclid mission of the European Space Agency seeks to understand the Universe’s expansion history and the nature of dark energy, through measurements of cosmic shear. This requires a very accurate estimate of the true redshift distribution of the galaxies, with the systematic error in the mean redshift satisfying σ⟨z⟩ < 0.002(1 + z) per tomographic bin. Achieving this accuracy relies on reference samples with spectroscopic redshifts, together with a procedure to match them to survey sources for which only photometric redshifts are available. One important source of systematic uncertainty is the mismatch in photometric properties between galaxies in the Euclid survey and the reference objects. We develop a method to degrade the photometry of objects with deep photometry to match the properties of any shallower survey in the multi-band photometric space, preserving all the correlations between the fluxes and their uncertainties. We compare our transfer method with more demanding image-based methods, such as Balrog from the Dark Energy Survey Collaboration. According to our metrics, our method outperforms Balrog. We implement our method in the redshift distribution reconstruction, based on the self-organising map approach, and test it using a realistic sample from the Euclid Flagship Mock Galaxy Simulation. We find that the key ingredient is to ensure that the reference objects are distributed in the colour space the same way as the wide-survey objects, which can be efficiently achieved with our transfer method. In our best implementation, the mean redshift biases are consistently reduced across the tomographic bins, bringing a significant fraction of them within the Euclid accuracy requirements in all tomographic bins. Equally importantly, the tests allow us to pinpoint which step in the calibration pipeline has the strongest impact on achieving the required accuracy. Our approach also reproduces the overall redshift distributions, which are crucial for applications such as angular clustering. The agreement between the reconstructed and true distributions demonstrates both the feasibility and robustness of the approach. This implementation is sufficient for Euclid Data Release 1 and provides a solid foundation for subsequent data releases.

Abstract:

This study explores the impact of observational and modelling systematic effects on cluster number counts and cluster clustering and provides model prescriptions for their joint analysis in the context of the Euclid survey. Using 1000 Euclid -like cluster catalogues, we investigated the effect of systematic uncertainties on cluster summary statistics and their auto- and cross-covariance, and performed a likelihood analysis to evaluate their impact on cosmological constraints, with a focus on the matter density parameter (Ω m ) and on the power spectrum amplitude ( σ 8 ). Combining cluster clustering with number counts significantly improves cosmological constraints, with the figure of merit increasing by over 300% compared to number counts alone. We confirm that the two probes are uncorrelated, and the cosmological constraints derived from their combination are almost insensitive to the cosmology dependence of the covariance. We find that photometric redshift uncertainties broaden cosmological posteriors by 20–30%, while secondary effects such as redshift-space distortions (RSDs) have a smaller impact on the posteriors – 5% for clustering alone, 10% when combining probes – but can significantly bias the constraints if neglected. We show that clustering data below 60 h −1 Mpc provides additional constraining power, while scales larger than the acoustic oscillation scale add almost no information on Ω m and σ 8 parameters. The RSDs and photo- z uncertainties also influence the number count covariance, with a significant impact of about 15–20% on the parameter constraints.

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.