Euclid

Abstract:

The Euclid large-scale weak-lensing survey aims to trace the evolution of cosmic structures up to redshift z ∼ 3 and beyond. Its success depends critically on obtaining highly accurate mean redshifts for ensembles of galaxies n ( z ) in all tomographic bins, essential for deriving robust cosmological constraints. However, photometric redshifts (photo- z s) are affected by systematic biases, arising from various sources of uncertainty and dominated by selection effects of the spectroscopic sample used for calibration. To address these challenges, we utilised self-organising maps (SOMs) with mock samples resembling the Euclid Wide Survey (EWS) from the Flagship2 simulation, to validate Euclid ’s uncertainty requirement of |Δ⟨ z ⟩| = ⟨ z est ⟩−⟨ z ⟩≤0.002(1 + z ) per tomographic bin, assuming DR3-level data. Consequently, we identify the most effective galaxy selection for our tomographic bins, while systematically examining the implementation of quality control cuts to reduce sources of uncertainty. In particular, we observe that defining the redshift tomography using the mean spectroscopic redshift (spec- z ) per SOM cell, results in none of the ten tomographic redshift bins satisfying the requirement. In contrast, the redshift tomography on the photo- z s of the EWS-like sample yields superior results, with eight out of ten bins [0 < z ≤ 2.5] meeting the Euclid requirement. To enhance the realism of our study, we morph our calibration sample to mimic the C3R2 survey in incremental steps. In this context, a maximum of six out of ten bins meet the requirement, strongly advocating the adoption of a redshift tomography defined by the photo- z s of individual galaxies rather than the commonly used mean spec- z of SOM cells. To examine the impact on the expected biases for Ω m , σ 8 , and Δ w 0 measured by Euclid , we perform a Fisher forecast for cosmic shear only, based on our redshift uncertainties. Here, we find that even under an evaluation of the uncertainty where the impact of the redshift bias is substantial, most absolute biases remain below 0.1 σ in the idealised scenario and below 0.3 σ in the more realistic case.

Abstract:

The galaxy cluster XLSSC 122 is a rare system at z = 1.98, hosting surprisingly evolved member galaxies when the Universe was only one-third of its present age. Leveraging deep JWST/NIRCam imaging, we perform a weak-lensing analysis and reconstruct the cluster’s mass distribution, finding a mass peak that coincides with both the X-ray peak and the position of the brightest cluster galaxy. Consistent with recent strong-lensing analyses, we obtain a mass estimate of 1.60 ± 0.30 (stat.) ± 0.26 (LSS) × 1014 M⊙ and an implied concentration of c200c = 6.3 ± 0.4, where the uncertainty represents the propagation of the mass error through the adopted concentration–mass relation and excludes intrinsic scatter. Placing our weak-lensing mass map in the context of Chandra X-ray data, MeerKAT radio imaging, Atacama Large Millimeter/submillimeter Array + Atacama Compact Array/Atacama Cosmology Telescope Sunyaev–Zel’dovich (SZ) mapping, and new JWST intracluster light measurements, we identify consistent NE–SW elongation across datasets and a pronounced offset along the same axis between the SZ and mass/X-ray peaks, pointing to significant merger activity. XLSSC 122 thus serves as a JWST pilot study for high-z lensing, demonstrating the telescope’s unique ability to map cluster mass distributions at z ∼ 2. The concordance of the multiwavelength analysis here, together with the high concentration relative to ΛCDM expectations, motivates a uniform sample of analogous systems with joint lensing, X-ray, SZ, and radio data to probe cluster assembly at cosmic noon.

Abstract:

As radio emission from normal galaxies is a dust-free tracer of star formation, tracing the star formation history of the Universe is a key goal of the Square Kilometre Array and the Next-Generation Very Large Array. In order to investigate how well radio luminosity traces star formation rate (SFR) in the early Universe, we have examined the radio properties of a JWST Paα sample of galaxies at 1.0 ≲ z ≲ 1.8. In the GOODS-S field, we cross-matched a sample of 506 FRESCO Paα emitters with the 1.23 GHz radio continuum data from the MeerKAT MIGHTEE survey, finding 47 detections. After filtering for active galactic nuclei (via X-ray detections, hot mid-infrared dust, and extended radio emission), as well as blended sources, we obtained a sample of star-forming galaxies comprising 11 cataloged radio detections, 18 noncataloged detections (at ≈3σ–5σ), and 298 undetected sources. Stacking the 298 undetected sources, we obtain a 3.3σ detection in the radio. This sample, along with a local sample of Paα emitters, lies along previous radio luminosity/SFR relations from local (<0.2) to high redshift (z ∼ 1). Fitting the FRESCO data at 1.0 ≲ z ≲ 1.8, we find log(L1.4GHz)= (1.31 ± 0.17) × log(SFRPaα)+ (21.36 ± 0.17), which is consistent with other literature relations. We can explain some of the observed scatter in the L1.4GHz/SFRPaα correlation by a toy model in which the synchrotron emission is a delayed/averaged tracer of the instantaneous Paα SFR by ∼10/75 Myr.

Abstract:

ABSTRACT We study the spatially resolved star formation, gas ionization, and outflow properties of 1813 active galactic nuclei (AGNs) from the MaNGA survey, which we classify into infrared (IR), broad-line (BL), narrow-line (NL), and radio (RD) AGNs based on their mid-infrared colours, optical spectra, and/or radio photometry. We also provide estimations of AGN power at different wavelengths. AGN incidence is found to increase with stellar mass following a power law, with the high-mass end dominated by RDAGNs and the low-mass end dominated by NLAGNs. Compared to their mass-matched non-AGN counterparts, we find that IRAGNs, BLAGNs, and NLAGNs on average show enhanced specific star formation rates, younger stellar populations, and harder ionization towards the centre. RDAGNs, in contrast, show radial profiles similar to quiescent galaxies. [O iii] outflows are more common and stronger in BL/IRAGNs, while RDAGNs on average show no outflow features. The outflow incidence increases with [O iii] luminosity, and the features in BL/IRAGNs on average extend to $\sim$2 kpc from the nuclei. We further discuss a possible evolutionary sequence of AGNs and their host galaxies, where AGNs with strong emission lines or dust tori are present in star-forming galaxies. Later, young compact radio jets emerge, the host galaxies gradually quench, and the AGN hosts eventually evolve into globally quiescent systems with larger radio jets that prevent further gas cooling.

Abstract:

Deep radio continuum surveys provide fundamental constraints on galaxy evolution, but source confusion limits sensitivity to the faintest sources. We present a complete framework for producing high-fidelity deblended radio catalogues from the confused MIGHTEE maps using the probabilistic deblending framework XID+ and prior positions from deep multi-wavelength data in the COSMOS field. To assess performance, we construct MIGHTEE-like simulations based on the Tiered Radio Extragalactic Continuum Simulation radio source population, ensuring a realistic distribution of star-forming galaxies and active galactic nuclei for validation. Through these simulations, we show that prior catalogue purity is the dominant factor controlling deblending accuracy: a high-purity prior, containing only sources with a high likelihood of radio detection, recovers accurate flux densities and reproduces input source counts down to (where thermal noise). On the other hand, a complete prior overestimates the source counts due to spurious detections. Our optimal strategy combines the high-purity prior with a mask that removes sources detected above Jy. Applied to the 1.3 deg area of the MIGHTEE-COSMOS field defined by overlapping multi-wavelength data, this procedure yields a deblended catalogue of 89 562 sources. The derived 1.4 GHz source counts agree with independent P(D) analyses and indicate that we resolve the radio background to Jy. We also define a recommended high-fidelity sample of 20 757 sources, based on detection significance, flux density, and goodness-of-fit, which provides reliable flux densities for individual sources in the confusion-limited regime.