Anthony H. Gonzalez

We present the construction and characterization of a multiwavelength catalog of galaxy groups and clusters by matching optical detections from the Southern Photometric Local Universe Survey (S-PLUS) with extended X-ray emission from the first eROSITA all-sky survey data release (eRASS1). We employed a probabilistic matching framework, based on the modified Hausdorff distance, to associate galaxy systems identified by the PZWav cluster finder and characterized by the AME membership estimator with X-ray surface brightness contours. This method explicitly accounts for the photometric redshift probability distribution of galaxies and allowed us to explore the critical trade-off between catalog completeness and purity. We investigated the change in the matched sample with different optical selection depths, defined by absolute magnitude cuts of M _r < -18.5, −19, and −19.5, and −20 sampling redshifts within 0.08 < z < 0.25, and for purity levels of 80%, 90%, and 95%. Fainter optical cuts enhance the recovery of low-mass low-luminosity groups, while brighter cuts favor more massive clusters and increase the effective survey volume at higher redshifts. Stricter purity requirements reduce contamination, but systematically lower completeness, particularly for low-luminosity systems. The derived X-ray luminosity functions agree well with previous determinations, and the log N –log S distributions confirm the high recovery rate of luminous clusters. Comparisons with the redMaPPer cluster catalog validate our approach, showing consistent trends and significant overlap, while our method offers improved completeness at the group scale. This work demonstrates a robust, flexible method for creating reliable multiwavelength cluster catalogs, which is essential for cosmological studies and investigations of galaxy evolution in dense environments.

The first Euclid Quick Data Release (Q1) contains millions of galaxies with excellent optical and near-infrared (IR) coverage. To complement this dataset, we investigate the average far-IR properties of Euclid -selected main sequence (MS) galaxies using existing Herschel and SCUBA-2 data. We used 17.6 deg ² (2.4 deg ² ) of overlapping Herschel (SCUBA-2) data, containing 2.6 million (240 000) MS galaxies. We binned the Euclid catalogue by stellar mass and photometric redshift and performed a stacking analysis following SimStack , which accounts for galaxy clustering and bin-to-bin correlations. We detected stacked far-IR flux densities across a significant fraction of the bins. We fitted modified blackbody spectral energy distributions in each bin and derived mean dust temperatures ( T _d ), dust masses ( M _d ), and star-formation rates (SFRs). We find similar mean SFRs compared to the Euclid catalogue, and we show that the average dust-to-stellar mass ratios decreased from z ≃ 1 to the present day. Average dust temperatures are largely independent of stellar mass and are well-described by the function T ₂ + ( T ₁ − T ₂ ) e ^{− t / τ} , where t is the age of the Universe, T ₁ = (79.7 ± 7.4) K, T ₂ = (23.2 ± 0.1) K, and τ = (1.6 ± 0.1) Gyr. We argue that since the dust temperatures converge to a non-zero value below z = 1, the dust is now primarily heated by the existing cooler and older stellar population, as opposed to hot young stars in star-forming regions at higher redshifts. We show that since the dust temperatures are independent of stellar mass, the correlation between dust temperature and SFR depends on stellar mass. Lastly, we estimate the contribution of the Euclid catalogue to the cosmic IR background (CIB), finding that it accounts for > 60% of the CIB at 250, 350, and 500 μm. As the Euclid mission progresses, larger catalogues will allow us to probe the far-IR properties of MS galaxies out to higher redshifts and lower stellar masses, potentially recovering the complete CIB.

The well-known bimodality between star-forming discs and quiescent spheroids requires the existence of two main processes: galaxy quenching, causing the strong reduction of star formation, and morphological transformation, causing the transition from disc-dominated structures to bulge-dominated ones. In this paper, we aim to understand the link between these two processes and their relation with the stellar mass of galaxies and their local environment. Taking advantage of the first data released by the Euclid Collaboration, covering more than 60 deg ² with space-based imaging and photometry, we analyse a mass-complete sample of nearly one million galaxies in the range 0.25 < z < 1 with M _* > 10 ^9.5 M _⊙ , using a combination of photometric and spectroscopic redshifts. We divide the sample into four sub-populations of galaxies, based on their star-formation activity (star-forming and quiescent) and morphology (disc-dominated and bulge-dominated). We then analyse the physical properties of these populations and their relative abundances in the stellar mass versus local density plane. Together with confirming the passivity-density relation and the morphology-density relation, we find that quiescent discy galaxies are more abundant in the low-mass regime of high-density environment where log ₁₀ (1 + δ ) > 1.3. At the same time, star-forming bulge-dominated galaxies are more common in field regions with log ₁₀ (1 + δ ) < 0.8, preferentially at high masses. Building on these results and interpreting them through comparison with simulations, we propose a scenario where the evolution of galaxies in the field significantly differs from that in higher-density environments. The morphological transformation in the majority of field galaxies takes place before the onset of quenching and is mainly driven by secular processes taking place within the main sequence, leading to the formation of star-forming bulge-dominated galaxies as intermediate-stage galaxies. Conversely, quenching of star formation precedes morphological transformation for most galaxies in higher-density environments. This causes the formation of quiescent disc-dominated galaxies before their transition into bulge-dominated ones.

We present the first catalogue of strong-lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering 63.1 deg ² ). This catalogue is the result of the visual inspection of 1260 Euclid image cutouts of previously identified galaxy clusters. Each galaxy cluster was assigned a lensing score, 𝒫 _lens , derived from the aggregated votes of multiple visual inspectors, the majority of whom possess extensive expertise in strong gravitational lensing. Votes were assigned based on the assessed credibility and plausibility of the identified strong-lensing features. Specifically, we identified 83 gravitational lenses with 𝒫 _lens > 0.5, of which 14 have 𝒫 _lens = 1 and clearly exhibit secure strong-lensing features, such as giant tangential and radial arcs, and multiple images. Considering the measured number density of lensing galaxy clusters, approximately 0.3 deg ⁻² for 𝒫 _lens > 0.9, we predict that Euclid will likely observe more than 4500 strong-lensing clusters over the course of the mission. Notably, only three of the identified cluster-scale lenses had previously been observed from space. Thus, Euclid has provided the first high-resolution imaging for the remaining 80 strong-lensing galaxy cluster candidates, including those with the highest scores. The identified strong-lensing features will be used to train deep-learning models to automatically identify gravitational arcs and multiple images in the Euclid observations. This study confirms the great potential of Euclid for finding new strong-lensing clusters, enabling exciting new discoveries on the nature of dark matter and dark energy and the study of the high-redshift Universe.

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 z _phot ∼ 1.65 candidate cluster. It was also detected independently as a z _phot ∼ 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 H _E ≤ 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 × 10 ¹¹ 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.

The extent to which the environment affects galaxy evolution has been under scrutiny by researchers for decades. With the first data from Euclid, we can begin to systematically study a wide range of environments and their effects as a function of redshift, using 63, ^2 of space-based data. In this paper, we present results from the Euclid Quick Data Release, where we measured the passive-density and morphology-density relations in the redshift range z=0.25--1. We determined if a galaxy is passive using the specific star formation rate, and we classified the morphologies of galaxies using the Sérsic index n and the u-r colours. We measured the local environmental density of each galaxy using the N . This result is indicative of the separability of the effects from the stellar mass and the environment. Similarly, at all redshifts in this work, the early-type galaxy fraction increases with increasing density at fixed stellar mass, meaning the environment also transforms the morphology of the galaxy independently of stellar mass, up to M_* łesssim 10^ deg neighbour method. We find that at a fixed stellar mass, the quenched fraction (the fraction of galaxies that have ceased star formation) increases with increasing local environmental density up to z=1 10.8 M_⊙. For M_* 10.8 M_⊙, almost all galaxies are early-types, with minimal impact from the environment. At z>0.75, the morphology depends mostly on stellar mass, with only low-mass galaxies being affected by the environment. Given that the morphology classifications use u-r colours, these are correlated to the star formation rate, and as such our morphology results should be taken with caution, yet future morphology classifications should help verify these results. To summarise, we successfully identify the passive-density and morphology-density relations at 0.25<z<1. Future Euclid data releases are key to confirm these trends at higher redshifts.

We present our methodology for identifying known clusters as counterparts to objects in the Euclid Catalogue of Galaxy Clusters (ECGC). Euclid is expected to detect a large number of optically selected galaxy clusters over the approximately square degrees of its extragalactic sky survey. Extending out well beyond redshift unity, the catalogue will contain many new high-redshift clusters, while at lower redshifts a fraction of the clusters will have been observed in other surveys. Identifying these known clusters as counterparts to the Euclid-detected clusters is an important step in the validation and construction of the ECGC to augment information with external observables. We present a set of catalogues and meta-catalogues of known clusters that we have assembled for this step, and we illustrate their application and our methodology using the Dark Energy Survey Year 1 cluster catalogue in lieu of the future ECGC. In the process of this work, we have constructed and delivered an updated catalogue with multi-wavelength counterparts. 14000 RedMaPPer EC-RedMaPPer

We leverage JWST’s superb resolution to derive strong-lensing mass maps of 14 clusters, spanning a redshift range of z ∼ 0.25–1.06 and a mass range of M ₅₀₀ ∼ 2–12 × 10 ¹⁴ M _⊙ , from the Strong LensIng and Cluster Evolution (SLICE) JWST program. These clusters represent a small subsample of the first clusters observed in the SLICE program that are chosen based on the detection of new multiple-image constraints in the SLICE JWST NIRCam/F150W2 and F322W2 imaging. These constraints include new lensed dusty galaxies and new substructures in previously identified lensed background galaxies. Four clusters have never been modeled before. For the remaining 10 clusters, we present updated models based on JWST and Hubble Space Telescope imaging and, where available, ground-based spectroscopy. We model the global mass profile for each cluster and report the masses enclosed within 200 and 500 kpc. We report the number of new lensed source galaxies identified in the JWST imaging, which in one cluster is as high as 19 new lensed galaxies. The addition of new lensed source galaxies and constraints from substructure clumps improves the ability of strong-lensing models to accurately reproduce the interior mass distribution of each cluster. We also report the discovery of a candidate transient in a lensed image of the galaxy cluster SPT-CL J0516-5755. All lens models and their associated products are available for download at the Strong Lensing Cluster Atlas Data Base ( https://data.lam.fr/sl-cluster-atlas/ ), which is hosted at Laboratoire d’Astrophysique de Marseille.

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust automated methods capable of handling the immense data volume generated. In this work, we present an advanced deep learning (DL) framework based on mask region-based convolutional neural networks (Mask R-CNNs) designed to autonomously detect and segment bright strongly lensed arcs in Euclid's multi-band imaging of galaxy clusters. The model was trained on a realistic simulated dataset of cluster-scale SL events constructed by injecting mock background sources into Euclidised Space Telescope images of ten massive lensing clusters, exploiting their high-precision mass models constructed with extensive spectroscopic data. The network was trained and validated on over 4500 simulated images and tested on an independent set of 500 simulations as well as on as real Euclid Quick Data Release (Q1) observations. The trained network achieves a high performance in identifying gravitational arcs in the test set, with a precision and recall of 76% and 58%, respectively, processing 2' , is open source and is available at . Hubble 2' images in a fraction of a second. When applied to a sample of visually confirmed Euclid Q1 cluster-scale lenses, our model recovers ≈ 66% of the gravitational arcs above the area threshold used during training. While the model shows promising results, limitations include the production of some false positives and challenges in detecting smaller, fainter arcs. Our results demonstrate the potential of advanced DL computer vision techniques for efficient and scalable arc detection in the effort towards enabling automated analysis of SL systems in current and future wide-field surveys. The code, ARTEMIDE https://github.com/LBasz/ARTEMIDE