Research Articles (Physics)

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Mixing of structures in100zr studied via β decay
(Jagiellonian University, 2026) Kalaydjieva, Desislava; Bildstein, V; Garrett, P.E; Zielińska, M; Stoychev, K; Rocchini, M; Pannu, S; Bidaman, H; Korten, W; Vedia, V; Garnsworthy, A.B; Ahmed, Z; Andreoiu, C; Annen, D.W; Asch, H; Avaa, A.A; Ball, G.C; Benzoni, G; Bhattacharjee, S.S; Buck, S; Coleman, R.J; Devinyak, S; Dillmann, I; Dowie, J; Caballero-Folch, R; Garcia, F.H; Geerlof, E.D; Greaves, B; Griffin, C.J; Grimes, A.L; Grinyer, G.F; Gyabeng Fuakye, E; Hackman, G; Hicks, S; Hymers, D; Kanungo, R; Kapoor, K; Karayonchev, V; Kasanda, E; Lange, S; Lenardo, B; Maqungo, Lwazikazi; Marchini, N; Marlow, B; Martin, M.S; Mashtakov, K.M; Murillo Morales, S; Murias, J.R; Nannini, A; Natzke, C; Olaizola, B; Ortner, K; Peters, E; Petrache, C.M; Polletini, M; Porzio, C; Radich, A.J; Richardson, G; Saei, N; Satrazani, M; Scheck, M; Siciliano, M; Singh, M; Spagnoletti, P; Svensson, C.E; Taddei, E; Tocabens, G; Torres, D.A; Triambak, Smarajit; Umashankar, R; Valbuena, S; Wu, F; Zidar, T
Properties of low-lying states in100Zr were studied using the GRIFFIN spectrometer at TRIUMF following the β decay of100Y. Using γ–γ angular correlations, level spins were confirmed and E2/M1 mixing ratios determined with improved precision. Applicability of a two-state mixing model to the observed structures in100Zr is explored.
Euclid quick data release (q1) Xix. First study of red quasars selection
(EDP Sciences, 2026) Karagiannis , Dionysios; Tarsitano , Federica; Fotopoulou , Sotiria; Banerji , Manda
Red quasars constitute an important but elusive phase in the evolution of supermassive black holes, where dust obscuration can significantly alter their observed properties. They have broad emission lines, like other quasars, but their optical continuum emission is significantly reddened, which is why they were traditionally identified based on near- and mid-infrared selection criteria. This work showcases the capability of the Euclid space telescope to find a large sample of red quasars, using Euclid near infrared (NIR) photometry. We first conduct a forecast analysis, comparing a synthetic catalogue of red quasars with COSMOS2020. Using template fitting, we reconstruct Euclid-like photometry for the COSMOS sources and identify a sample of candidates in a multi-dimensional colour-colour space achieving 98% completeness for mock red quasars with 30% contaminants. To refine our selection function, we implement a probabilistic Random Forest classifier, and use UMAP visualisation to disentangle non-linear features in colour-space, reaching 98% completeness and 88% purity. A preliminary analysis of the candidates in the Euclid Deep Field Fornax (EDF-F) shows that, compared to VISTA+DECam-based colour selection criteria, Euclid’s superior depth, resolution, and optical-to-NIR coverage improves the identification of the reddest, most obscured sources. Notably, the Euclid exquisite resolution in the IE filter unveils the presence of a candidate dual quasar system, highlighting the potential for this mission to contribute to future studies on the population of dual AGN. The resulting catalogue of candidates, including more the 150 000 sources, provides a first census of red quasars in Euclid Q1 and sets the groundwork for future studies in the Euclid Wide Survey (EWS), including spectral follow-up analyses and host morphology characterisation
Euclid quick data release (Q1): XV. A probabilistic classification of quenched galaxies
(EDP Sciences, 2026) Karagiannis, Dionysios; Corcho-Caballero, Pablo; Ascasibar, Yago
Investigating what drives the quenching of star formation in galaxies is key to understanding their evolution. The Euclid mission will provide rich spatial and spectral data from optical to infrared wavelengths for millions of galaxies, and enable precise measurements of their star formation histories. Using the first Euclid Quick Data Release (Q1), we developed a probabilistic classification framework that combines the average specific star-formation rate (sSFRlog(τ)) inferred over two timescales (τ = 108, 109 yr) to categorise galaxies as ‘ageing’ (secularly evolving), ‘quenched’ (recently halted star formation), or ‘retired’ (dominated by old stars). We validated this methodology using synthetic observations from the IllustrisTNG simulation. Two classification methods were employed: a probabilistic approach, which integrates posterior distributions, and a model-driven method, which optimises sample purity and completeness using IllustrisTNG. At z < 0.1 and M* ≳ 3 × 108 M⊙, we obtain Euclid class fractions of 68–72%, 8–17%, and 14–19% for ageing, quenched, and retired populations, respectively, which is consistent with previous studies. Ageing and retired galaxies dominate at the low- and high-mass end, respectively, while quenched galaxies surpass the retired fraction for M* ≲ 1010 M⊙. The evolution with redshift shows increasing and decreasing fractions of ageing and retired galaxies, respectively. The fraction of quenched systems shows a weaker dependence on stellar mass and redshift, varying between 5 and 15%. We find tentative evidence that more massive galaxies usually undergo quenching episodes at earlier times with respect to their low-mass counterparts. We analysed the mass-size-metallicity relation for each population. Ageing galaxies generally exhibit disc morphologies and low metallicities. Retired galaxies show compact structures and enhanced chemical enrichment, while quenched galaxies form an intermediate population that is more compact and chemically evolved than ageing systems. Despite potential selection biases, this work demonstrates Euclid’s great potential for elucidating the physical nature of the quenching mechanisms that govern galaxy evolution.
Euclid Quick Data Release (Q1): XXXII. From simulations to sky: Advancing machine-learning lens detection with real Euclid data
(EDP Sciences, 2026) Lines, Natalie; Collett, Thomas; Karagiannis, Dionysios
In the era of large-scale surveys such as 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 led 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 the Euclid 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 the Euclid Data Release 1 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 the Vera Rubin Observatory’s Legacy Survey of Space and Time.
Euclid quick data release (Q1) XXVI. The strong lensing discovery engine A – system overview and first lens sample
(EDP Sciences, 2026) Karagiannis, Dionysios; Walmsley, Mike; Holloway, Philip
We present a catalogue of 497 galaxy-galaxy strong lenses in the Euclid Quick Release 1 data (63 deg2). In the initial 0.45% of Euclid’s surveys, we double the total number of known lens candidates with space-based imaging. Our catalogue includes 250 grade A candidates, the vast majority of which (243) were previously unpublished. Euclid’s resolution reveals rare lens configurations of scientific value, including double-source-plane lenses, edge-on lenses, complete Einstein rings, and quadruply imaged lenses. We resolve lenses with small Einstein radii (θE < 1″) in large numbers for the first time. These lenses were found through an initial sweep by deep learning models followed by Space Warps citizen scientist inspection, expert vetting, and system-by-system modelling. Our search approach scales straightforwardly to Euclid Data Release 1 and, without changes, would yield approximately 7000 high-confidence (grade A or B) lens candidates by late 2026. Further extrapolating to the complete Euclid Wide Survey implies a likely yield of over 100 000 high-confidence candidates, transforming strong lensing science.
Euclid quick data release (Q1): VII. Characteristics and limitations of the spectroscopic measurements
(EDP Sciences, 2026) Karagiannis, Dionysios; Le Brun, Vincent; Béthermin, Matthieu
The spectroscopy processing function (SPE PF) of the Euclid pipeline is dedicated to the automatic analysis of 1D spectra to determine redshifts, line fluxes, and spectral classifications. The first Euclid Quick Data Release (Q1) delivers these measurements for all HE < 22.5 objects identified in the photometric survey. In this paper, we present an overview of the SPE PF algorithm and assess its performance by comparing its results with high-quality spectroscopic redshifts from the Dark Energy Spectroscopic Instrument (DESI) survey in the Euclid Deep Field North. Our findings highlight remarkable accuracy in successful redshift measurements, with a bias of less than 3 × 10−5 in (zSPE − zDESI)/(1 + zDESI) and a high precision of approximately 10−3. The majority of spectra have only a single spectral feature or none at all. To avoid spurious detections, whereby noise features are misinterpreted as lines or lines are misidentified, it is therefore essential to apply well-defined criteria on quantities such as the redshift probability, or the Hα flux, and signal-to-noise ratio. Using a well-tuned quality selection, we achieve an 89% redshift success rate in the target redshift range for cosmology (0.9 < z < 1.8), which is well covered by DESI for z < 1.6. Outside this range in which the Hα line is observable, redshift measurements are less reliable, except for sources showing specific spectral features (e.g. two bright lines or strong continuum). The classification based on spectroscopy alone is effective for galaxies (about 80% success rate), while it is less efficient for stars and quasars (< 60%). Ongoing refinements along the entire chain of PFs are expected to enhance both redshift measurements and spectral classification, allowing us to define the large and reliable sample required for cosmological analyses. Taking into account the planned evolution of the spectroscopic pipeline, partially based on the limitations identified in this paper, these results are encouraging for Euclid’s future galaxy clustering measurements, even though the requirements are not yet fulfilled.
Euclid Quick Data Release (Q1): V. Photometric redshifts and physical properties of galaxies through the PHZ processing function
(EDP Sciences, 2026) Karagiannis, Dionysios; Tucci, Marco; Paltani, Stéphane
The ESA Euclid mission will measure the photometric redshifts of billions of galaxies to provide an accurate 3D view of the Universe at optical and near-infrared wavelengths. Photometric redshifts are determined by the PHotometric redshift (PHZ) processing function on the basis of the multi-wavelength photometry of Euclid and ground-based observations. In this paper, we describe in detail the so-called PHZ processing used for the first ‘quick’ (Q1) Euclid data release, along with the output products and their validation with respect to the Euclid requirements. The PHZ pipeline is responsible for the following main tasks: i) source classification into star, galaxy, and quasar (or QSO) classes based on photometric colours; ii) determination of photometric redshifts for the core science; and iii) determination of physical properties of galaxies for non-cosmological science. The classification is able to provide a star sample with a high level of purity, a highly complete galaxy sample, and reliable probabilities of belonging to those classes. The identification of QSOs is instead more problematic: photometric information available in the Euclid Wide Survey alone seems to be insufficient to accurately separate QSOs from galaxies. The performance of the pipeline in the determination of photometric redshifts has been tested using the COSMOS2020 catalogue and a large sample of spectroscopic redshifts. The results in both cases are in line with expectations: the precision of the estimates are compatible with Euclid requirements; however, as expected, a bias correction is needed to achieve the accuracy level required for the cosmological probes. Finally, the pipeline provides reliable estimates of the physical properties of galaxies, in good agreement with findings from the COSMOS2020 catalogue – apart from an unrealistically large fraction of very young galaxies with very high specific star-formation rates. However, the application of appropriate priors is sufficient to obtain reliable physical properties for those problematic objects. We present several areas for improvement for future Euclid data releases.
Euclid quick data release (Q1)IX. First visual morphology catalogue
(EDP Sciences, 2026) Karagiannis , Dionysis; Walmsley, Mike; Huertas-Company, Marc
We present a detailed visual morphology catalogue for the Euclid Quick Release 1 (Q1). Our catalogue includes galaxy features such as bars, spiral arms, and ongoing mergers, for the 378 000 bright (IE < 20:5) or extended (area 700 pixels) galaxies in Q1. The catalogue was created by finetuning the Zoobot galaxy foundation models on annotations from an intensive one-month campaign by Galaxy Zoo volunteers. Our measurements are fully automated, and hence fully scaleable. This catalogue is the first 0.4% of the approximately 100 million galaxies where Euclid will ultimately resolve detailed morphology
Euclid quick data release (Q1) XXXIV. First detections from the Euclid galaxy cluster workflow
(EDP Sciences, 2026) Karagiannis , Dionysis; Bhargava, Sunayana; Benoist, Christophe
The first survey data release by the Euclid mission covers approximately 63 deg2 in the Euclid Deep Fields to the same depth as the Euclid Wide Survey. This paper showcases, for the first time, the performance of cluster finders on Euclid data and presents examples of validated clusters in the Quick Release 1 (Q1) imaging data. We identify clusters using two algorithms (AMICO and PZWav) implemented in the Euclid cluster-detection pipeline. We explore the internal consistency of detections from the two codes, and cross-match detections with known clusters from other surveys using external multi-wavelength and spectroscopic data sets. This enables assessment of the Euclid photometric redshift accuracy and also of systematics such as mis-centring between the optical cluster centre and centres based on X-ray and/or Sunyaev–Zeldovich observations. We report 426 joint PZWav and AMICO-detected clusters with high signal-to-noise ratios over the full Q1 area in the redshift range 0:2 z 1:5. The chosen redshift and signal-to-noise thresholds are motivated by the photometric quality of the early Euclid data. We provide richness estimates for each of the Euclid-detected clusters and show its correlation with various external cluster mass proxies. Due to the limited area and evolving data quality, the sample is not intended to serve as a reference for cosmological applications, but to verify and validate the cluster workflow. Out of the full sample, 77 systems are potentially new to the literature. Overall, the Q1 cluster catalogue demonstrates a successful validation of the workflow ahead of the Euclid Data Release 1, based on the consistency of internal and external properties of Euclid-detected clusters.
Euclid quick data release (Q1) XXI. Active galactic nuclei identification using diffusion-based inpainting of Euclid VIS images
(EDP Sciences, 2026) Karagiannis , Dionysis; Stevens, Grant; Fotopoulou, Sotiria
Light emission from galaxies exhibit diverse brightness profiles, influenced by factors such as galaxy type, structural features, and interactions with other galaxies. Elliptical galaxies feature more uniform light distributions, while spiral and irregular galaxies have complex, varied light profiles due to their structural heterogeneity and star-forming activity. In addition, galaxies with active galactic nuclei (AGN) feature intense, concentrated emission from gas accretion around supermassive black holes, superimposed on regular galactic light, while quasi-stellar objects (QSOs) represent extreme cases in which AGN emissions dominate their host galaxies. The challenge of identifying AGN and QSOs has been discussed many times in the literature, often requiring multi-wavelength observations. This paper introduces a novel approach to identify AGN and QSOs from a single image. Diffusion models have recently been developed in the machine-learning literature to generate realistic-looking images of everyday objects. Utilising the spatial resolving power of the Euclid VIS images, we created a diffusion model trained on one million sources, without using any source pre-selection or labels. The model learns to reconstruct light distributions of normal galaxies, since the population is dominated by them. We conditioned the prediction of the central light distribution by masking the central few pixels of each source and reconstructed the light according to the diffusion model. We further used this prediction to identify sources that deviate from this profile by examining the reconstruction error of the few central pixels regenerated in each source’s core. Our approach, solely using VIS imaging, features high completeness compared to traditional methods of AGN and QSO selection, including optical, near-infrared, mid-infrared, and X-rays. Our study offers practical insights for refining diffusion models and broadening their applications throughout the Euclid survey area, underscoring the utility of this approach in diverse astronomical contexts beyond just AGN identification.
A direct detection of neutral hydrogen intensity mapping on mpc scales at z ≈ 0.32 and z ≈ 0.44
(American Astronomical Society, 2026) Paul, Sourabh; Chen, Zhaoting; Santos, Mario G.; Wolz, Laura
We report the detection of the cosmological power spectrum using the intensity mapping signal from 21 cm emission of neutral hydrogen (H I), derived from interferometric observations with the L-band receivers of the MeerKAT radio telescope. Intensity mapping is a promising technique to map the three-dimensional matter distribution of the Universe at radio frequencies and probe the underlying cosmology. So far, detections have only been achieved through cross-correlations with galaxy surveys. Here we present independent measurements of the H I power spectrum at redshifts 0.32 and 0.44 with the foreground avoidance method. We utilize two distinct frameworks for mitigating systematics: a conservative baseline-flagging-based approach achieves detections at 3.2σ and 3.5σ, and a power-spectrum-based flagging method enhances the significance to 5.9σ and 9.18σ, respectively. The information contained in the power spectrum measurements allows us to probe the parameters of the H I mass function and H I halo model. These results are a significant step toward precision cosmology with H I intensity mapping using the new generation of radio telescopes. © 2026. The Author(s). Published by the American Astronomical Society. Original content from this work may be used under the terms of the https://creativecommons.org/licenses/by/4.0/. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Euclid quick data release (Q1): X. a census of dwarf galaxies across a range of distances and environments
(EDP Sciences, 2026) Marleau, Francine; Karagiannis, Dionysis; Habas, Rebecca
The Euclid Q1 fields were selected for calibration purposes in cosmology and are therefore relatively devoid of nearby galaxies. However, this is precisely what makes them interesting fields in which to search for dwarf galaxies in local density environments. We took advantage of the unprecedented depth, spatial resolution, and field of view of the Euclid Quick Release (Q1) to build a census of dwarf galaxies in these regions. We have identified dwarf galaxies in a representative sample of 25 contiguous tiles in the Euclid Deep Field North (EDF-N) covering an area of 14.25 deg2. The dwarf galaxy candidates were identified using a semi-automatic detection method based on properties measured by the Euclid pipeline and released as part of the catalogue produced by the MERge Processing Function (MER PF) pipeline. A selection cut in surface brightness and magnitude was used to produce an initial dwarf candidate catalogue, and this was followed by a cut in morphology (removing background spirals) and IE − HE colour (removing red ellipticals). This catalogue was then visually classified to produce a final sample of dwarf candidates, including their morphology, number of nuclei, globular cluster (GC) richness, and presence of a blue compact centre. We identified 2674 dwarf candidates, corresponding to 188 dwarfs per square degree. The visual classification of the dwarfs reveals a slightly uneven morphological mix of 58% ellipticals and 42% irregulars, with very few potentially GC-rich (1.0%) and nucleated (4.0%) candidates but a noticeable fraction (6.9%) of dwarfs with blue compact centres. The distance distribution of 388 (15%) of the dwarf candidates with spectroscopic redshifts peaks at about 400 Mpc. Their stellar mass distribution confirms that our selection effectively identifies dwarfs while minimising contamination. The most prominent dwarf overdensities are dominated by dwarf ellipticals, while dwarf irregulars are more evenly distributed across the field of view. This work highlights Euclid’s remarkable ability to detect and characterise dwarf galaxies across diverse masses, distances, and environments.
Euclid quick data release (Q1): XXXI. LEMON – lens modelling with neural networks. automated and fast modelling of euclid gravitational lenses with singular isothermal ellipsoid mass profile
(EDP Sciences, 2026) Busillo, Valerio; Karagiannis, Dionysis; Tortora, Crescenzo
The Euclid mission aims to survey around 14 000 deg2 of extragalactic sky, providing around 105 gravitational lens images. Modelling of gravitational lenses is fundamental to estimate the total mass of the lens galaxy, along with its dark matter content. Traditional modelling of gravitational lenses is computationally intensive and requires manual input. In this paper, we use a Bayesian neural network, LEns MOdelling with Neural networks (LEMON), to model Euclid gravitational lenses with a singular isothermal ellipsoid mass profile. Our method estimates key lens mass profile parameters, such as the Einstein radius, while also predicting the light parameters of foreground galaxies and their uncertainties. We validate LEMON’s performance on both mock Euclid datasets, real lenses observed with Hubble Space Telescope (HST) that have been degraded to match observations with the same depth of the Euclid Wide Survey, and real Euclid lenses, demonstrating the ability of LEMON to predict parameters of both simulated and real lenses. Results show promising accuracy and reliability in predicting the Einstein radius, mass and light ellipticities, effective radius, Sérsic index, lens magnitude, and unlensed source position for simulated lens galaxies. The application to real data, including the latest Quick Release 1 strong lens candidates, provides encouraging results in the recovery of the parameters for real lenses. We also verified that LEMON has the potential to accelerate traditional modelling methods, by giving to the classical optimiser the LEMON predictions as starting points, resulting in a speed-up of up to 26 times the original time needed to model a sample of gravitational lenses, a result that would be impossible with randomly initialised guesses. Moreover, LEMON can be used to cross-validate results from the traditional modelling methods, and thus has the potential to reduce the failure rate of the Euclid modelling pipeline. This work represents a significant step towards efficient, automated gravitational lens modelling, which is crucial for handling the large data volumes expected from Euclid.
Euclid quick data release (Q1): II. VIS processing and data products
(EDP Sciences, 2026) McCracken, Henry Joy; Karagiannis, Dionysis; Benson, Kevin
This paper describes the VIS processing function (VIS PF) of the Euclid ground segment pipeline, which processes and calibrates raw data from the VIS camera. We present the algorithms used in each processing element along with a description of the on-orbit performance of VIS PF based on performance verification and Q1 datasets. We demonstrate that the principal performance metrics (image quality, astrometric accuracy, photometric calibration) are within pre-launch specifications. The image-to-image photometric scatter is less than 0.8% and absolute astrometric accuracy compared to Gaia is 5 mas. Image quality is stable over all Q1 images, with a full width at half maximum (FWHM) of 0.″16. The stacked images (combining four nominal and two short exposures) reach IE = 25.6 (10σ, measured as the variance of 1.″3 diameter apertures). We also describe quality control metrics provided with each image, and an appendix provides a detailed description of the provided data products. The excellent quality of these images demonstrates the immense potential of Euclid VIS data for weak lensing. VIS data covering most of the extragalactic sky will provide a lasting high-resolution atlas of the Universe.
Euclid quick data release (Q1): IV. From images to multi-wavelength catalogues: the euclid merge processing function★
(EDP Sciences, 2026) Romelli, Erik; Karagiannis, Dionysis; Kümmel, Martin
The Euclid satellite is an ESA mission that was launched in July 2023. Euclid is working in its regular observing mode with the target of observing an area of 14 000 deg2 with two instruments, the Visible Camera (VIS) and the Near IR Spectrometer and Photometer (NISP) down to IE = 24.5 mag (10 σ) in the Euclid Wide Survey. Ground-based imaging data in the ugriz bands complement the Euclid data to enable photo-z determination and VIS PSF modelling for weak lensing analysis. Euclid investigates the distance-redshift relation and the evolution of cosmic structures by measuring the shapes and redshifts of galaxies and clusters of galaxies out to z ∼ 2. Generating the multi-wavelength catalogues from Euclid and ground-based data is an essential part of the Euclid data processing system. In the framework of the Euclid Science Ground Segment (SGS), the aim of the MERge Processing Function (MER PF) pipeline is to detect objects in the Euclid imaging data, measure their properties, and merge them into a single multi-wavelength catalogue. The MER PF pipeline performs source detection on both visible (VIS) and near-infrared (NIR) images and offers four different photometric measurements: Kron total flux, aperture photometry on PSF-matched images, template fitting photometry, and Sérsic fitting photometry. Furthermore, the MER PF pipeline measures a set of ancillary quantities, spanning from morphology to quality flags, to better characterise all detected sources. In this paper, we show how the MER PF pipeline is designed, detailing its main steps, and we show that the pipeline products meet the tight requirements that Euclid aims to achieve on photometric accuracy. We also present the other measurements (e.g., morphology) that are included in the OU-MER output catalogues and we list all output products coming out of the MER PF pipeline.
Euclid Quick Data Release (Q1) XIII. Exploring galaxy properties with a multi-modal foundation model
(EDP Sciences, 2026) Karagiannis, Dionysios; Siudek, Małgorzata; Huertas-Company, Marc
Modern astronomical surveys, such as the Euclid mission, produce high-dimensional, multi-modal datasets that include imaging and spectroscopic information for millions of galaxies. These data serve as an ideal benchmark for large, pre-trained multi-modal models, which can leverage vast amounts of unlabelled data. In this work, we present the first exploration of Euclid data with AstroPT, an autoregressive multi-modal foundation model trained on approximately 300000 optical and infrared Euclid images and spectral energy distributions (SEDs) from the first Euclid Quick Data Release. We compare self-supervised pre-training with baseline fully supervised training across several tasks: galaxy morphology classification; redshift estimation; similarity searches; and outlier detection. Our results show that: (a) AstroPT embeddings are highly informative, correlating with morphology and effectively isolating outliers; (b) including infrared data helps to isolate stars, but degrades the identification of edge-on galaxies, which are better captured by optical images; (c) simple fine-tuning of these embeddings for photometric redshift and stellar mass estimation outperforms a fully supervised approach, even when using only 1% of the training labels; and (d) incorporating SED data into AstroPT via a straightforward multi-modal token-chaining method improves photo-z predictions, and allow us to identify potentially more interesting anomalies (such as ringed or interacting galaxies) compared to a model pre-trained solely on imaging data. © The Authors 2026. Open Access article, https://www-edpsciences-org.ezproxy.uwc.ac.za, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This article is published in open access under the https://www-aanda-org.ezproxy.uwc.ac.za/subscribe-to-open-faqs. mailto:subscribers@edpsciences.org to support open access publication.
Euclid Quick Data Release (Q1) XII. Quenching precedes bulge formation in dense environments but follows it in the field
(EDP Science, 2026) Karagiannis, Dionysios; Gentile, Fabrizio; Daddi, Emmanuele
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 deg2 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* > 109.5 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 log10(1 + δ) > 1.3. At the same time, star-forming bulge-dominated galaxies are more common in field regions with log10(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. © The Authors 2026. Open Access article, https://www-edpsciences-org.ezproxy.uwc.ac.za, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This article is published in open access under the https://www-aanda-org.ezproxy.uwc.ac.za/subscribe-to-open-faqs. mailto:subscribers@edpsciences.org to support
Euclid quick data release (q1): xxiv. Extending the quest for little red dots to z < 4
(EDP Sciences, 2026) Bisigello L.; Rodighiero G.; Fotopoulou S.; Ricci F.; Jahnke K.
ecent observations with the James Webb Space Telescope (JWST) have revealed an interesting population of sources with a compact morphology and a characteristic v-shaped continuum, namely blue at a rest frame λ < 4000 Å and red at longer wavelengths. The nature of these sources, which are called little red dots (LRDs), is still highly debated because it is unclear whether they host active galactic nuclei (AGNs) and their number seems to drop drastically at z < 4. We took advantage of the 63 deg2 covered by the Euclid Quick Data Release (Q1) to extend the search for LRDs to brighter magnitudes and lower redshifts than what was possible with JWST. This is fundamental for a broader view of the evolution of this peculiar galaxy population. The selection was performed by fitting the available photometric data (Euclid, the Spitzer Infrared Array Camera (IRAC), and ground-based griz data) with two power laws to retrieve the rest-frame optical and UV slopes consistently over a wide redshift range (i.e. z < 7.6). We then excluded extended objects and possible line emitters and inspected the data visually to remove any imaging artefacts. The final selection included 3341 LRD candidates from z = 0.33 to z = 3.6, 29 of which were also detected in IRAC. The resulting rest-frame UV luminosity function, in contrast with previous JWST studies, shows that the number density of LRD candidates increases from high redshift to z = 1.5–2.5 and decreases at even lower redshifts. The subsample of more robust LRD candidates that are also detected with IRAC show a weaker evolution, however, which is affected by low statistics and limited by the IRAC resolution. The comparison with previous quasar UV luminosity functions shows that LRDs are not the dominant AGN population at z < 4 and MUV < −21. Follow-up studies of these LRD candidates are pivotal to confirm their nature, probe their physical properties, and determine whether they are compatible with JWST sources because the different spatial resolution and wavelength coverage of Euclid and JWST might select different samples of compact sources.
Interpretable machine learning of halo gas density profiles: a sensitivity analysis of cosmological hydrodynamical simulations
(National University of Ireland Maynooth, 2026) Davé, Romeel; Sorini, Daniele; Bose, Sownak; Bose, Sownak
Stellar and AGN-driven feedback processes affect the distribution of gas on a wide range of scales, from within galaxies well into the intergalactic medium. Yet, it remains unclear how feedback, through its connection to key galaxy properties, shapes the radial gas density profile in the host halo. We tackle this question using suites of the EAGLE, IllustrisTNG, and Simba cosmological hydrodynamical simulations, which span a variety of feedback models. We develop a random forest algorithm that predicts the radial gas density profile within haloes from the total halo mass and five global properties of the central galaxy: gas and stellar mass; star formation rate; mass and accretion rate of the central black hole (BH). The algorithm reproduces the simulated gas density profiles with an average accuracy of ∼83–90% over the halo mass range 109.5 M⊙ < M200c < 1015 M⊙ and redshift interval 0 < z < 4. For the first time, we apply Sobol statistical sensitivity analysis to full cosmological hydrodynamical simulations, quantifying how each feature affects the gas density as a function of distance from the halo centre. Across all simulations and redshifts, the total halo mass and the gas mass of the central galaxy are the most strongly tied to the halo gas distribution, while stellar and BH properties are generally less informative. The exact relative importance of the different features depends on the feedback scenario and redshift. Our framework can be readily embedded in semi-analytic models of galaxy formation to incorporate halo gas density profiles consistent with different hydrodynamical simulations. Our work also provides a proof of concept for constraining feedback models with future observations of galaxy properties and of the surrounding gas distribution.
Euclid Quick Data Release (Q1) XXII. An investigation of optically faint, red objects in the Euclid Deep Fields
(EDP Sciences, 2026) Karagiannis, Dionysios; Girardi, Giorgia; Rodighiero, Giulia
Our understanding of cosmic star formation at z > 3 used to largely rely on rest-frame UV observations. However, these observations overlook dusty and massive sources, resulting in an incomplete census of early star-forming galaxies. Recent infrared data from Spitzer and the James Webb Space Telescope (JWST) have revealed a hidden population at z ∼ 3−6 with extreme red colours. Taking advantage of the overlap between imaging of the Euclid Deep Fields (EDFs), covering about 60 deg2 , and ancillary Spitzer observations, we identified 27 000 extremely red objects with HE − IRAC2 > 2.25 (dubbed HIEROs) down to a 10σ completeness magnitude limit of IRAC2 = 22.5 AB. After a visual investigation to discard artefacts and any objects with troubling photometry, we were left with a final sample of 3900 candidates. We retrieved the physical parameter estimates for these objects from the spectral energy distribution-fitting tool CIGALE. Our results confirm that HIERO galaxies can populate the high-mass end of the stellar mass function at z > 3, with some sources reaching extreme stellar masses (M∗ > 1011 M ) and exhibiting high dust attenuation values (AV > 3). However, we consider the stellar mass estimates unreliable for sources at z > 3.5. For this reason, we favour a more conservative lower-z solution. The challenges faced by spectral energy distribution-fitting tools in accurately characterising these objects underscore the need for further studies that incorporate both observations at shorter wavelengths and spectroscopic data. Euclid spectra will help resolve degeneracies and better constrain the physical properties of the brightest galaxies. Given the extreme nature of this population, characterising these sources is crucial for building a comprehensive picture of galaxy evolution and stellar mass assembly across most of the history of the Universe. This work demonstrates Euclid’s potential to provide statistical samples of rare objects, such as massive, dust-obscured galaxies at z > 3, which will be prime targets for JWST and the Atacama Large Millimeter/submillimeter Array (ALMA).

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