Euclid

Abstract:

Stellar bars are key structures in disc galaxies, driving angular momentum redistribution and influencing processes such as bulge growth and star formation. Quantifying the bar fraction as a function of redshift and stellar mass is therefore important for constraining the physical processes that drive disc formation and evolution across the history of the Universe. Leveraging the unprecedented resolution and survey area of the Euclid Q1 data release, combined with the Zoobot deep-learning model trained on citizen science labels, we identified (7711) barred galaxies with (M_* ≳ 10^ M_⊙) in a magnitude-selected sample ((I_E < 20.5)) spanning (63.1 deg ^2). We measured a mean bar fraction of (0.2-0.4), consistent with previous studies. At fixed redshift, massive galaxies exhibit higher bar fractions, while lower-mass systems show a steeper decline with redshift, suggesting earlier disc assembly in massive galaxies. Comparisons with cosmological simulations (e.g. TNG50 Auriga ) reveal a broadly consistent bar fraction, but highlight overpredictions for high-mass systems, pointing to potential over-efficiency in central stellar mass build-up in simulations. A semi-empirical model ( Decode ) in which bar formation is regulated by the gas fraction broadly reproduces the observed bar fractions. These findings demonstrate the transformative potential of Euclid for galaxy morphology studies and underscore the importance of refining theoretical models to better reproduce observed trends. Future work will explore finer mass bins, environmental correlations, and additional morphological indicators.

Abstract:

We present three catalogues of candidate active galactic nuclei (AGN) in the Euclid Quick Release (Q1) fields. For each Euclid source, we collected multi-wavelength photometric and spectroscopic information from surveys such as the Galaxy Evolution Explorer (GALEX) the Dark Energy Survey (DES), the Wide-field Infrared Survey Explorer (WISE) Spitzer the Dark Energy Spectroscopic Instrument (DESI), and the Sloan Digital Sky Survey (SDSS), including spectroscopic redshifts from public compilations when available. We investigated the AGN content of the Q1 fields using multiple selection methods. Applying Euclid colours and WISE-AllWISE cuts, we identified 292,222 and 65,131 candidates, respectively. We compiled a high-purity QSO catalogue based on DR3 information, containing 1971 candidates. Using spectroscopic information from DESI, we performed broad-line and narrow-line AGN selections, yielding 4392 AGN candidates across the Q1 fields. We investigated and refined the Euclid Q1 probabilistic random forest QSO population, selecting a refined sample of 180,666 candidates. Additionally, we performed spectral energy distribution (SED) fitting on sources with available z_ spec and utilising the derived AGN fraction, we identified 7766 AGN candidates. To improve the purity of the selection, we defined two new colour criteria (JH_I_E Y and I_E H_gz), finding 313,714 and 267,513 candidates, respectively, across the Q1 fields. We have found a total of 229,779 AGN candidates equivalent to an AGN surface density of 3641 deg^-2 for $18< 24.5$ and a subsample of 30,422 candidates corresponding to an AGN surface density of 482 deg^-2 when limiting the depth to $18< 22$. The AGN surface densities recovered are consistent with predictions based on AGN X-ray luminosity functions.

Abstract:

Studying the radio spectral energy distribution (SED) of distant galaxies is essential for understanding their assembly and evolution over cosmic time. We present rest-frame radio SEDs of a sample of 160 star-forming galaxies at 1.5 < z < 3.5 in the Cosmic Evolution Survey field as part of the MeerKAT International GHz Tiered Extragalactic Exploration project. MeerKAT observations combined with archival Very Large Array and Giant Metrewave Radio Telescope data allow us to determine the integrated mid-radio (ν = 1–10 GHz) continuum (MRC) luminosity and magnetic field strength. A Bayesian method is used to model the SEDs and to separate the free–free and synchrotron emission. We also calibrate the star formation rate (SFR) in radio both directly through SED analysis and indirectly through the infrared–radio correlation (IRRC). With a mean value of αnt ≃ 0.7, the synchrotron spectral index flattens with both redshift and specific SFR, indicating that cosmic rays are more energetic in the early Universe due to higher star formation activity. The magnetic field strength increases with redshift, B ∝ (1 + z)(0.7±0.1), and SFR as B ∝ SFR0.3, suggesting a small-scale dynamo acting as its main amplification mechanism. Taking into account the evolution of the SEDs, the IRRC is redshift invariant, and it does not change with stellar mass at 1.5 < z < 3.5, although the correlation deviates from linearity. Similarly, we show that the SFR traced using the integrated MRC luminosity is redshift invariant.

Abstract:

We show, using the pseudo-Cl technique, how to estimate cosmic shear and galaxy–galaxy lensing power spectra that are insensitive to the effects of multiple sources of lensing bias including source-lens clustering, magnification bias, and obscuration effects. All of these effects are of significant concern for ongoing and near-future Stage-IV cosmic shear surveys. Their common attribute is that they all introduce a cosmological dependence into the selection of the galaxy shear sample. Here, we show how a simple adaptation of the pseudo-Cl method can help to suppress these biases to negligible levels in a model-independent way. Our approach is based on making pixelized maps of the shear field and then using a uniform weighting of those shear maps when extracting power spectra. To produce unbiased measurements, the weighting scheme must be independent of the cosmological signal, which makes the commonly used inverse-variance weighting scheme unsuitable for cosmic shear measurements. We demonstrate this explicitly. A frequently cited motivation for using inverse-variance weights is to minimize the errors on the resultant power spectra. We find that, for a Stage-IV-like survey configuration, this motivation is not compelling: the precision of power spectra recovered from uniform-weighted maps is only very slightly degraded compared to those recovered from an inverse-variance analysis, and we predict no degradation in cosmological parameter constraints. We suggest that other 2-point statistics, such as real-space correlation functions, can be rendered equally robust to these lensing biases by applying those estimators to pixelized shear maps using a uniform weighting scheme.