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P. Gómez-Alvarez

Publications and source records attributed to P. Gómez-Alvarez.

At least 19 recordsLinked to original sources
arXiv2026

Euclid Quick Data Release (Q1). The first Euclid view of Planck galaxy protocluster candidates at cosmic noon

[ABRIGED ABSTRACT] A large catalogue of candidate galaxy protoclusters with high star-formation rates was produced by the Planck collaboration. We search, in the first data release (Q1) of the Euclid survey, for the visible and infrared counterparts of the Planck galaxy protocluster candidates expected to be above $z > 1.5$. Eight of them are in Euclid Q1. Our goal is to investigate the optical nature of these overdensities previously detected in the submillimetre wavelength range. We search for overdensities using the DETECTIFz algorithm, an overdensity finder based on Delaunay tessellation that uses photometric redshift probability distributions through Monte Carlo simulations. Focusing our search on the eight high-star forming Planck protocluster candidates, we find that two of them have one Euclid counterpart, and six have between two and four Euclid counterparts, which amounts to a total of 20 Euclid counterparts. These Euclid counterparts lie at photometric redshifts $1.4<z_{\rm ph} < 2.7$ and 12 of them also have partial Herschel coverage. All detections have also been confirmed by at least one other independent protocluster detection algorithm. We study the colours, derived stellar masses and star-formation rates (SFRs) of the detected member galaxies of those protocluster candidate counterparts. We also estimate the total stellar masses, SFRs, and the halo mass lower limits for all Euclid protocluster candidates. We find that in the dark matter halo mass ($M_{\rm h}$) / redshift plane, these Planck and Euclid overdense regions lie in the region $12.6 <\log_{10} (M_{\rm h}/M_\odot)< 13.4$, $1.4<z< 2.7$. This means that the halos of our objects are expected to have experienced a transition between cold flows in hot media to accretion of hot material.

astro-ph.CO↗
arXiv2026

MEGARA Stellar Spectral Library. Second Release

We present the second release of the MEGARA spectral library, MEGASTAR, which now includes all spectra collected during ten observing semesters at the Gran Telescopio CANARIAS. This new release supersedes our first release and incorporates a substantial number of additional observations (2000 new spectra), obtained at high spectral resolution, R(FWHM)$\sim$20000, in two wavelength ranges centred on H$α$ (6420 - 6790 A) and on the CaII triplet (8370 - 8885 A). The aim of this paper is to introduce MEGASTAR DR2 to the community as its high-resolution spectra can serve as a valuable resource for numerous types of research. In particular, we will use MEGASTAR spectra to construct SSP blocks within the HR-PyPopStar evolutionary synthesis models. The stars were observed using the integral field spectroscopy mode of the instrument. We process the data in a uniform way with the MEGARA data reduction pipeline. We estimate the stellar flux by adding the spectra from 37 spaxels, centred on the spaxel with the highest flux in the IFU reconstructed image. This approach guarantees that the effective slit width, and therefore the spectral resolution, are the same for all spectra. The second MEGASTAR release consists of 2838 spectra corresponding to 1408 stars, providing a better coverage of the stellar parameter space than the first release. The spectra were acquired with an average continuum S/N of about 215. This second release meets the standards of a modern empirical library: it offers reliable calibrations, data free from slit effects, observations of a large number of stars, and provides high spectral resolution to model both individual stellar clusters and entire galaxies observed with MEGARA.

astro-ph.SR↗
arXiv2026

Euclid: Galaxy cluster detection through the weak lensing effect - algorithm assessment and selection

Weak gravitational lensing offers a powerful way to detect galaxy clusters by directly tracing their total matter content. Its effectiveness increases with the density of background galaxies, a requirement that is now being met by the high sensitivity and wide coverage of current large-area surveys. A prime example is the Euclid telescope, which will map approximately 14 000 deg2 of the sky, measuring the shapes of billions of galaxies and opening a meaningful window for detecting galaxy clusters uniquely through their weak lensing signal. We present the results of nine galaxy cluster detection algorithms in a blind challenge, using 1200 deg2 of Euclid-like weak lensing observations from the DEMNUni-Cov simulations. The performance of these methods was assessed by matching their detections to known synthetic clusters with signal-to-noise ratios greater than 2, satisfying the z-M selection cut, and adopting two different matching procedures. The purpose of the challenge was to identify and improve strategies for galaxy cluster detection via weak lensing for the upcoming Euclid data releases. We pre-selected four methods based on their individual performance and complementarity. Each pre-selected method adopts a distinct approach: AMICO-WL uses an optimal filtering technique, DoG employs Gaussian filtering, O21 relies on aperture-mass filtering, and W234 applies multi-scale wavelet filtering. Together, the results of these methods can be merged to enhance the processing of Euclid data. Individually, these algorithms reach approximately 10% completeness for a mean purity of 90%, while their combination leads to roughly a two-fold improvement in overall performance, exceeding 70% completeness for low-redshift, high-mass clusters. When extrapolating the results of this work to Euclid Data Release 1, we expect to detect approximately 2500 galaxy clusters via weak gravitational lensing.

astro-ph.CO↗
arXiv2026

Euclid: Quick Data Release (Q1) -- Exploring the detailed visual morphology of galaxies in clusters

Galaxy clusters provide unique laboratories for studying environmental effects on galaxy evolution. The morphology--density ($T$--$Σ$) and morphology--cluster-centric radius ($T$--$R$) relations trace how galaxy morphology is influenced by the environment, but previous studies at intermediate redshifts have been limited in both sample size and radial coverage. We use the Euclid Quick Data Release 1 (Q1) visual morphology catalogue to measure the $T$--$Σ$ and $T$--$R$ relations for smooth, featured-or-disc, and barred galaxies in known clusters at $0.2\leq z\leq 0.5$, extending this analysis to large cluster-centric distances ($3 R_{500c}$) and studying their dependence on stellar mass. Using photometric redshifts and stellar masses provided by Euclid, we identify 1754 cluster members within $1.5 R_{500c}$, distributed across 71 clusters. We classify the identified galaxies as smooth, featured-or-disc, or barred using the predicted vote fractions provided by the Zoobot deep learning foundation model in the Q1 visual morphology catalogue. We confirm the $T$--$Σ$ relation in all the stellar mass ranges studied, with a stronger influence of the cluster environment on galaxy morphology in the densest parts of the cluster and closer to the cluster centre. Beyond $1.5 R_{500c}$, the morphological segregation weakens, with featured-or-disc galaxies overtaking smooth galaxies at the lowest densities, consistent with the growing contribution of field interlopers in the cluster outskirts. For barred galaxies, we find a tentative decline of the bar fraction toward lower densities that is most pronounced for the most massive galaxies. In conclusion, our results show that the cluster environment drives a progressive transformation of galaxy morphology, with the loss of disc structure becoming more pronounced towards the cluster core, where environmental processes act most efficiently.

astro-ph.GA↗
arXiv2026

Euclid: Calibrating distances from surface brightness fluctuations with Early Release Observations of the Fornax cluster

Surface brightness fluctuations (SBF), the pixel-to-pixel variations in flux that arise from the statistical distribution of stars in galaxy images, provide a powerful tool to measure redshift-independent distances from photometric data alone. This method is particularly important in the era of large imaging surveys, such as those carried out during the Euclid mission. Here we present the first application of SBF to Euclid data, using the FAST-SBF code to measure stellar fluctuation amplitudes in the $I_\mathrm{E}$ band for a sample of galaxies in the Early Release Observations (ERO) of the Fornax galaxy cluster. Although the Euclid data reduction pipeline is not optimized for SBF measurements, extensive testing suggests that we are able to extract robust results. We calibrate the absolute fluctuation magnitude $\overline{M}_\mathrm{IE}$ as a function of the $(I_\mathrm{E}{-}H_\mathrm{E})$ colour for 15 galaxies in Fornax, then test this relation on galaxies in two other ERO fields: the Perseus cluster and dwarf satellite candidates around NGC 6744. Overall, we find reasonable agreement with distances in the literature and good agreement in cases where FAST-SBF indicates the measurements are robust. Finally, we compare our results against Stellar Population Tools (SPoT) simple stellar population models, and discuss the possibility of using SBF with Euclid to probe the underlying stellar populations of the galaxies.

astro-ph.GA↗
arXiv2026

Euclid: Measuring the intrinsic alignment of galaxies around cosmic voids in the \Euclid Flagship simulation\

We present a methodology to measure the intrinsic alignment (IA) signal of galaxies in the vicinity of cosmic voids using the \Euclid-like Flagship cosmological simulation from the Euclid Consortium. The IA signal is quantified and compared with the predictions of the linear alignment (LA) model, providing one of the first detailed investigations of this effect in underdense large-scale environments. While the IA signal around cosmic voids has received little attention to date, it may constitute a non-negligible systematic in forthcoming cosmological analyses that exploit void-lensing measurements. Our analysis examines red and blue galaxy populations separately, enabling a comparison of their alignment behaviour in void environments with the corresponding trends measured in galaxy-galaxy correlations. We find that the redshift evolution of the IA amplitude in cosmic voids is broadly consistent with that measured in the general galaxy population for both colour-selected samples. Additionally, our modelling allows us to estimate the linear bias of voids, $b_{\rm V}(z)$ which characterises how cosmic voids trace the underlying dark-matter density field, for voids with radii in the range $10 < R_{\rm V}/(h^{-1} {\rm Mpc}) < 15$. The measured bias exhibits a positive trend with redshift, consistent with theoretical predictions for the clustering of underdense regions. These results highlight the importance of accurately modelling IA in void studies, both to mitigate systematic effects in void-lensing cosmology and to further improve our understanding of galaxy-environment interactions in low-density regions of the Universe.

astro-ph.CO↗
arXiv2026

Euclid: Precise inference of defocus wavefront error from image diffraction spike measurements

The success of the Euclid cosmological weak lensing measurements requires unprecedented knowledge of the point spread function (PSF) shape. Defocus wavefront errors induce variations in PSF size that directly bias inferred galaxy shapes. We present a rapid, model-independent estimator of the Euclid visible instrument defocus based on measuring subpixel shifts in diffraction spikes from bright stars, arising from the non-mirror-symmetric placement of the telescope spiders. This estimate requires no a-priori PSF model and can be directly inferred from individual survey exposures within seconds. We express defocus as the secondary mirror displacement along the optical axis, $Δz$, achieving a per-exposure precision of $σ(Δz) = 0.022\,μ\text{m}$ in standard Euclid wide-survey images, corresponding to a peak-to-valley optical-path difference of $0.75\,\text{nm}$. This sensitivity resolves thermally induced shifts, typically 0.1-0.3$\,μ\text{m}$, and enables tracking of temporal evolution and field-of-view variations when combining exposures within periods of stability. Since July 2024, the Euclid telescope has been exceptionally stable, while changes to defocus are effectively homogeneous across the field of view. By correlating defocus with PSF size, we find that the Euclid DR3 requirement of a fractional PSF size bias of $\left|ΔR_\mathrm{PSF}^2/R_\mathrm{PSF}^2\right|<10^{-3}$ corresponds to field-averaged secondary mirror displacements exceeding $\langle Δz_\mathrm{thr}\rangle = (0.0683 \pm 0.0024)\,μ\text{m}$. Our estimator provides a robust real-time monitoring tool, supplies a stringent prior for computationally intensive PSF model fitting, and is applicable not only to the Euclid telescope, but to other telescopes whose spider vanes are not mirror-symmetrically arranged.

astro-ph.CO↗
arXiv2026

Euclid Quick Data Release (Q2) -- The Euclid Galactic Bulge Survey

The Euclid Quick Data Release Q2 provides an unprecedented deep, wide-field, high-angular-resolution view of the inner Galactic bulge through the Euclid Galactic Bulge Survey (EGBS). Nine contiguous fields covering 4.8 deg$^2$ were observed with the VIS instrument over 24 hours in March 2025. Unlike the nominal Euclid survey strategy, the EGBS employed 16 dithered exposures of 400 s each, corresponding to a total integration time of 1.8 hours per field. Dedicated calibration observations were obtained to derive point spread functions (PSFs). The primary objective of the EGBS is gravitational microlensing, with high-angular-resolution imaging enabling lens-mass measurements to better than 10%. The survey provides an optical reference dataset for previously discovered microlensing events and future observations of the Galactic bulge. The Q2 data were processed with the VIS-PF pipeline. The non-standard observing strategy required dedicated calibration products, while the extreme stellar density necessitated modifications to the astrometric calibration and cosmic-ray detection procedures. These improvements have since been incorporated into later pipeline versions. We describe the motivation, observing strategy, data processing, products, and first results of the EGBS. Astrometric residuals with respect to the Gaia DR3 catalogue are 5.5 mas in right ascension and 4.4 mas in declination across the survey area, while the photometric zero points are calibrated to 1.5%. The Q2 release includes calibrated single-dither images, dedicated PSF models, and photometric catalogues containing approximately 45 million detected sources per dither down to AB magnitude 26. Although incomplete because of extreme crowding, these products provide a robust astrometric and photometric foundation for future exploitation of the dataset.

astro-ph.GA↗
arXiv2026

Euclid Quick Data Release (Q1): The geometry of dark matter halos from extragalactic streams

Wide-field surveys like Euclid mark a new era of extragalactic stellar stream studies. With a large number of streams, it is now possible to constrain the dark matter halos of galaxies in a cosmological volume and draw comparisons to theoretical expectations for the geometry of dark matter halos. This study combines Euclid imaging with visual detection and segmentation annotations to analyse streams. We use projected stream morphologies to constrain the shape and centre-of-mass position (CoM) of each host galaxy's potential, jointly probing baryonic and dark matter distributions. These inferences complement weak lensing methods, with sensitivity to halo profile and geometry on sub-virial scales. The method enables both stacked, population-level constraints on halo flattening and CoM position, and constraints on these quantities for individual halos. We also present a novel method for transforming segmentation maps of stellar streams into smooth, curvature-preserving tracks optimised for fast and robust dynamical inference. This approach enables rapid modelling of stream morphology, supports a statistically rigorous combination of constraints across multiple streams within a single galaxy, and enables joint inference across galactic hosts. From our study of 13 galaxies with prominent tidal streams, we find agreement with spherical halos, albeit a mild preference for flattening with $q = 0.95^{+0.05}_{-0.10}$ at 68\% confidence. This is promising early agreement with $Λ$CDM predictions. With thousands more discovered streams expected across \Euclid's mission, our programme will enable precise measurements of halo shapes and CoM positions across large samples and redshifts, offering constraints on the geometry of dark matter halos.

astro-ph.GA↗
arXiv2026

Euclid Quick Data Release (Q1). The role of cosmic connectivity in shaping galaxy clusters

The matter distribution around galaxy clusters is distributed over several filaments, reflecting their positions as nodes in the large-scale cosmic web. The number of filaments connected to a cluster, namely its connectivity, is expected to affect the physical properties of clusters. Using the first Euclid galaxy catalogue from the Euclid Quick Release 1 (Q1), we investigate the connectivity of galaxy clusters and how it correlates with their physical and galaxy member properties. Around 220 clusters located within the three fields of Q1 (covering $\sim 63 \ \text{deg}^2$), are analysed in the redshift range $0.2 < z < 0.7$. Due to the photometric redshift uncertainty, we reconstruct the cosmic web skeleton, and measure cluster connectivity, in 2-D projected slices with a thickness of 170 comoving $h^{-1}.\text{Mpc}$ and centred on each cluster redshift, by using two different filament finder algorithms on the most massive galaxies ($M_*\ > 10^{10.3} \ M_\odot$). In agreement with previous measurements, we recover the mass-connectivity relation independently of the filament detection algorithm, showing that the most massive clusters are, on average, connected to a larger number of cosmic filaments, consistent with hierarchical structure formation models. Furthermore, we explore possible correlations between connectivities and two cluster properties: the fraction of early-type galaxies and the Sérsic index of galaxy members. Our result suggests that the clusters populated by early-type galaxies exhibit higher connectivity compared to clusters dominated by late-type galaxies. These preliminary investigations highlight our ability to quantify the impact of the cosmic web connectivity on cluster properties with Euclid.

astro-ph.CO↗
arXiv2026

Euclid: Photometric redshift calibration with the clustering redshifts technique

Aims: The precision of cosmological constraints from imaging surveys hinges on accurately estimating the redshift distribution $ n(z) $ of tomographic bins, especially their mean redshifts. We assess the effectiveness of the clustering redshifts technique in constraining Euclid tomographic redshift bins to meet the target uncertainty of $ σ( \langle z \rangle ) < 0.002 (1 + z) $. In this work, these mean redshifts are inferred from the small-scale angular clustering of Euclid galaxies, which are distributed into bins with spectroscopic samples localised in narrow redshift slices. Methods: We generate spectroscopic mocks from the Flagship2 simulation for the Baryon Oscillation Spectroscopic Survey (BOSS), the Dark Energy Spectroscopic Instrument (DESI), and Euclid's Near-Infrared Spectrometer and Photometer (NISP) spectroscopic survey. We evaluate and optimise the clustering redshifts pipeline, introducing a new method for measuring photometric galaxy bias (clustering), which is the primary limitation of this technique. Results: We have successfully constrained the means and standard deviations of the redshift distributions for all of the tomographic bins (with a maximum photometric redshift of 1.6), achieving precision beyond the required thresholds. We have identified the main sources of bias, particularly the impact of the 1-halo galaxy distribution, which imposed a minimal separation scale of 1.5 Mpc for evaluating cross-correlations. These results demonstrate the potential of clustering redshifts to meet the precision requirements for Euclid, and we highlight several avenues for future improvements.

astro-ph.CO↗
arXiv2026

Euclid preparation. Three-dimensional galaxy clustering in configuration space: Three-point correlation function estimation

Higher-order correlation functions are firmly established as a fundamental tool for the statistical analysis of clustering in modern galaxy surveys. It was demonstrated that they greatly enrich the information content extracted by two-point statistics, allowing us to break the degeneracies between model parameters and constrain departures from Gaussianity. This paper presents the statistical estimators adopted to evaluate the galaxy three-point correlation function and its numerical implementation within the data analysis pipeline of the Euclid Science Ground Segment. Two different algorithms are adopted to count triplets: a direct and exact counting method capable of providing a robust three-point correlation function measurement for any triangular configuration, and a more efficient method based on spherical harmonic decomposition, designed to address the computational challenges of measuring the three-point statistics for data sets as large as those of the final Euclid survey. The spherical harmonic decomposition estimates the Legendre coefficients of the three-point correlation function up to a finite expansion order. Despite being an approximation, the three-point function measured with this approach satisfies the scientific requirements of the mission. We also introduce, implement, and validate the random split technique, which reduces the computational cost of counting triplets in the reference random sample by a factor of 10, without significantly compromising numerical accuracy. We evaluated the robustness, precision, and accuracy of the numerical estimates through an extensive campaign of validation tests, the results of which are presented. Finally, we quantify the computational requirements and their scaling with the expected size of Euclid data set, showing that a complete three-point analysis of the final Euclid survey is within computational reach.

astro-ph.CO↗
arXiv2026

Euclid: Asteroid rotation periods from the Euclid Ecliptic Survey

The Euclid Ecliptic Survey was conducted during the calibration phase of the mission, 23-31 December 2023, as a campaign to study Solar System objects. We used data from this survey to analyse more than 23 000 appeareances of 2321 known asteroids. Due to their high apparent angular motion relative to the background stars (5-$60^{\prime\prime}\,\mathrm{h}^{-1}$), these objects appear as streaks in VIS long-exposure images. We set out to estimate their spin periods, since only $7\%$ of them have periods published in the literature. We used multiple apertures along each streak to increase the time resolution of our light curves. Our method combines a Lomb-Scargle approach with a Markov chain Monte Carlo (MCMC) algorithm to characterise the posterior distributions. Some asteroids show multimodality in the MCMC search, indicating period aliases; in these cases, we report all aliases and their likelihoods. We validate our pipeline by comparing our fitted periods with 48 published periods, including period harmonics. We find that $44\%$ of our periods are within $1\%$ of those published and $98\%$ are within $15\%$, and we establish that with $98\%$ confidence the best solution can be found among the first three aliases. All reliable periods reported agree with our current understanding of the spin-period distribution for asteroids. We find 16 periods below the spin barrier of 2.2 h with absolute magnitudes below 19, and thus 16 candidate super-fast rotators. We provide light curves for all 2321 objects observed and 889 high-quality periods in an open-access catalogue. The asteroids with reported periods include five Mars crossers, four Cybeles, four Hildas, three Hungarias, and 877 asteroids in other regions of the main belt. Our results represent the first batch of spin periods extracted from Euclid light curves and include the first-ever period measurements for $93\%$ of the objects.

astro-ph.EP↗
arXiv2026

Euclid: Galaxy morphology and photometry from bulge-disc decomposition of Early Release Observations

The background galaxies in Euclid ERO images of the Perseus cluster make up a remarkable sample in its combination of 0.57 deg$^2$ area, 25.3 and 23.2 AB mag depth, as well as 0.1" and 0.3" angular resolutions, in optical and near-IR bands, respectively. We perform a morphological analysis of 2445 and 12,786 galaxies with $I_E < 21$ and $I_E < 23$, respectively. We use single-Sérsic profiles and the sums of a Sérsic bulge and an exponential disc to model these galaxies with SourceXtractor++ and analyse their parameters in order to assess their consistencies and discrepancies. The fitted galaxies to $I_E < 21$ span the various Hubble types with ubiquitous bulge and disc components, and a bulge-to-total light ratio B/T taking all values from 0 to 1. The effective radius of the single-Sérsic profile is an intermediate estimate of galaxy size, between the bulge and disc effective radii, depending on B/T. The axis ratio of the single-Sérsic profile is higher than the disc axis ratio, increasingly so with B/T. The model impacts the photometry with -0.08 to 0.01 mag median systematic $I_E$ offsets between single-Sérsic and bulge+disc total magnitudes, and a 0.05 to 0.15 mag dispersion, from low to high B/T. We measure a median $0.3$ mag bulge-disc colour difference in rest-frame $M_g - M_i$ that originates from the disc-dominated galaxies, whereas bulge-dominated galaxies have similar median colours for their components. We also measure redder-inside disc colour gradients based on 5 to 10$\%$ systematic variations of disc effective radii between the optical and near-IR bands. This analysis demonstrates the usefulness and limitations of single-Sérsic profile modelling and the power of bulge-disc decomposition for characterising the morphology of lenticulars and spirals in Euclid images. We make available the catalogues of best-fit parameters for the morphological and SED fits.

astro-ph.GA↗
arXiv2026

Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification

We present an end-to-end, iterative pipeline for efficient identification of strong galaxy--galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalogues, we reject point sources, apply a magnitude cut (I$_E$ $\leq$ 24) on deflectors, and run a pixel-level artefact/noise filter to build 96 $\times$ 96 pix cutouts; VIS+NISP colour composites are constructed with a VIS-anchored luminance scheme that preserves VIS morphology and NISP colour contrast. A VIS-only seed classifier supplies clear positives and typical impostors, from which we curate a morphology-balanced negative set and augment scarce positives. Among the six CNNs studied initially, a modified VGG16 (GlobalAveragePooling + 256/128 dense layers with the last nine layers trainable) performs best; the training set grows from 27 seed lenses (augmented to 1809) plus 2000 negatives to a colour dataset of 30,686 images. After three rounds of iterative fine-tuning, human grading of the top 4000 candidates ranked by the final model yields 441 Grade A/B candidate lensing systems, including 311 overlapping with the existing Q1 strong-lens catalogue, and 130 additional A/B candidates (9 As and 121 Bs) not previously reported. Independently, the model recovers 740 out of 905 (81.8%) candidate Q1 lenses within its top 20,000 predictions, considering off-centred samples. Candidates span I$_E$ $\simeq$ 17--24 AB mag (median 21.3 AB mag) and are redder in Y$_E$--H$_E$ than the parent population, consistent with massive early-type deflectors. Each training iteration required a week for a small team, and the approach easily scales to future Euclid releases; future work will calibrate the selection function via lens injection, extend recall through uncertainty-aware active learning, explore multi-scale or attention-based neural networks with fast post-hoc vetters that incorporate lens models into the classification.

astro-ph.GA↗
arXiv2026

Euclid: Early Release Observations -- The star-formation history of massive early-type galaxies in the Perseus cluster

The Euclid Early Release Observations (ERO) programme targeted the Perseus galaxy cluster in its central region over 0.7deg$^2$. We combined the exceptional image quality and depth of the ERO-Perseus with FUV and NUV observations from GALEX and AstroSat/UVIT, as well as $ugrizHα$ data from MegaCam at the CFHT, to deliver FUV-to-NIR magnitudes of the 87 brightest galaxies within the Perseus cluster. We reconstructed the star-formation history (SFH) of 59 early-type galaxies (ETGs) within the sample, through the spectral energy distribution (SED) fitting code CIGALE and state-of-the-art stellar population (SP) models to reproduce the galactic UV emission from hot, old, low-mass stars (i.e. the UV upturn). In addition, for the six most massive ETGs in Perseus [stellar masses $\log_{10}(M_{\ast}/M_{\odot}) \geq 10.3$], we analysed their spatially resolved SP through a radial SED fitting. In agreement with our previous work on Virgo ETGs, we found that (i) the majority of ETGs needs the presence of an UV upturn to explain their FUV emission, with temperatures $\langle T_{\rm UV}\rangle$~33800 K; (ii) ETGs have grown their stellar masses quickly, with SF timescales $τ\lesssim 1500$ Myr. We found that all ETGs in the sample have formed more than about 30% of their stellar masses at z~5, up to ~100%. At z~5, the stellar masses of the most massive nearby ETGs, which have present-day stellar masses $\log_{10}(M_{\ast}/M_{\odot})\gtrsim 10.8$, are then found to be comparable to those of the red quiescent galaxies observed by JWST at similar redshifts (z>4.6). This study can be extended to ETGs in the 14000 deg$^2$ extragalactic sky that will soon be observed by Euclid, in combination with those from other major upcoming surveys (e.g. Rubin/LSST), and UV observations, to ultimately assess whether the nearby massive ETGs represent the progeny of the massive high-z JWST red quiescent galaxies.

astro-ph.GA↗
arXiv2025

Euclid: Quick Data Release (Q1) -- A photometric search for ultracool dwarfs in the Euclid Deep Fields

We present a catalogue of 5306 new ultracool dwarf (UCD) candidates in the three Euclid Deep Fields in the Q1 data release. They range from late M to late T dwarfs, and include 1200 L and T dwarfs. A total of 546 objects have been spectroscopically confirmed, including 329 L dwarfs and 26 T dwarfs. We also provide empirical Euclid colours as a function of spectral type. Our UCD selection criteria are based only on colour ($I_\mathrm{E}-Y_\mathrm{E}>2.5$). The combined requirement for optical detection and stringent signal-to-noise ratio threshold ensure a high purity of the sample, but at the expense of completeness, especially for T dwarfs. The detections range from magnitudes 19 and 24 in the near-infrared bands, and extend down to 26 in the optical band. We discuss Euclid's capability to identify UCD candidates based on its photometric passbands. The average surface density of detected UCDs on the sky is approximately 100 objects per $\mathrm{deg}^2$, including 20 L and T dwarfs per $\mathrm{deg}^2$. This leads to an expectation of at least 1.4 million ultracool dwarfs in the final data release of the Euclid Wide Survey, including at least $300\,000$ L dwarfs, and more than 2600 T dwarfs, using the strict selection criteria from this work.

astro-ph.SR↗
arXiv2025

Euclid Quick Data Release (Q1). From simulations to sky: Advancing machine-learning lens detection with real Euclid data

In the era of large-scale surveys like Euclid, machine learning has become an essential tool for identifying rare yet scientifically valuable objects, such as strong gravitational lenses. However, supervised machine-learning approaches require large quantities of labelled examples to train on, and the limited number of known strong lenses has lead to a reliance on simulations for training. A well-known challenge is that machine-learning models trained on one data domain often underperform when applied to a different domain: in the context of lens finding, this means that strong performance on simulated lenses does not necessarily translate into equally good performance on real observations. In Euclid's Quick Data Release 1 (Q1), covering 63 deg2, 500 strong lens candidates were discovered through a synergy of machine learning, citizen science, and expert visual inspection. These discoveries now allow us to quantify this performance gap and investigate the impact of training on real data. We find that a network trained only on simulations recovers up to 92% of simulated lenses with 100% purity, but only achieves 50% completeness with 24% purity on real Euclid data. By augmenting training data with real Euclid lenses and non-lenses, completeness improves by 25-30% in terms of the expected yield of discoverable lenses in Euclid DR1 and the full Euclid Wide Survey. Roughly 20% of this improvement comes from the inclusion of real lenses in the training data, while 5-10% comes from exposure to a more diverse set of non-lenses and false-positives from Q1. We show that the most effective lens-finding strategy for real-world performance combines the diversity of simulations with the fidelity of real lenses. This hybrid approach establishes a clear methodology for maximising lens discoveries in future data releases from Euclid, and will likely also be applicable to other surveys such as LSST.

astro-ph.IM↗