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G. Castignani

Publications and source records attributed to G. Castignani.

At least 127 records · Page 7Linked to original sources

Euclid Quick Data Release (Q1). A probabilistic classification of quenched galaxies

Investigating what drives the quenching of star formation in galaxies is key to understanding their evolution. The Euclid mission will provide rich 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 inferred over two timescales ($10^8,10^9$ yr) to categorise galaxies as `ageing' (secularly evolving), `quenched' (recently halted star formation), or `retired' (dominated by old stars). 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 $M_\ast \gtrsim 3\times10^{8}\,M_\odot$, we obtain Euclid class fractions of 68-72\%, 8-17\%, and 14-19\% for ageing, quenched, and retired populations, respectively. Ageing and retired galaxies dominate at the low- and high-mass end, respectively, while quenched galaxies surpass the retired fraction for $M_\ast \lesssim 10^{10}\,\rm M_\odot$. The evolution with redshift shows increasing and decreasing fractions of ageing and retired galaxies, respectively. More massive galaxies usually undergo quenching episodes at earlier times than to their low-mass counterparts. In terms of the mass-size-metallicity relation, 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. This work demonstrates Euclid's great potential for elucidating the physical nature of the quenching mechanisms that govern galaxy evolution.

astro-ph.GA↗

Euclid preparation: The flat-sky approximation for the clustering of Euclid's photometric galaxies

We compare the performance of the flat-sky approximation and Limber approximation for the clustering analysis of the photometric galaxy catalogue of Euclid. We study a 6 bin configuration representing the first data release (DR1) and a 13 bin configuration representative of the third and final data release (DR3). We find that the Limber approximation is sufficiently accurate for the analysis of the wide bins of DR1. Contrarily, the 13 bins of DR3 cannot be modelled accurately with the Limber approximation. Instead, the flat-sky approximation is accurate to below $5\%$ in recovering the angular power spectra of galaxy number counts in both cases and can be used to simplify the computation of the full power spectrum in harmonic space for the data analysis of DR3.

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Euclid Quick Data Release (Q1). Active galactic nuclei identification using diffusion-based inpainting of Euclid VIS images

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 an active galactic nucleus (AGN) feature intense, concentrated emission from gas accretion around supermassive black holes, superimposed on regular galactic light, while quasi-stellar objects (QSO) are the extreme case of the AGN emission dominating the galaxy. The challenge of identifying AGN and QSO has been discussed many times in the literature, often requiring multi-wavelength observations. This paper introduces a novel approach to identify AGN and QSO from a single image. Diffusion models have been recently 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 condition the prediction of the central light distribution by masking the central few pixels of each source and reconstruct the light according to the diffusion model. We further use 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.

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Euclid: Exploring observational systematics in cluster cosmology -- a comprehensive analysis of cluster counts and clustering

This study explores the impact of observational and modelling systematic effects on cluster number counts and cluster clustering and provides model prescriptions for their joint analysis, in the context of the \Euclid survey. Using 1000 \Euclid-like cluster catalogues, we investigate the effect of systematic uncertainties on cluster summary statistics and their auto- and cross-covariance, and perform a likelihood analysis to evaluate their impact on cosmological constraints, with a focus on the matter density parameter $Ω_{\rm m}$ and on the power spectrum amplitude $σ_8$. Combining cluster clustering with number counts significantly improves cosmological constraints, with the figure of merit increasing by over 300\% compared to number counts alone. We confirm that the two probes are uncorrelated, and the cosmological constraints derived from their combination are almost insensitive to the cosmology dependence of the covariance. We find that photometric redshift uncertainties broaden cosmological posteriors by 20--30\%, while secondary effects like redshift-space distortions (RSDs) have a smaller impact on the posteriors -- 5\% for clustering alone, 10\% when combining probes -- but can significantly bias the constraints if neglected. We show that clustering data below $60\,h^{-1}\,$Mpc provides additional constraining power, while scales larger than acoustic oscillation scale add almost no information on $Ω_{\rm m}$ and $σ_8$ parameters. RSDs and photo-$z$ uncertainties also influence the number count covariance, with a significant impact, of about 15--20\%, on the parameter constraints.

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Prospects for dark matter observations in dwarf spheroidal galaxies with the Cherenkov Telescope Array Observatory

The dwarf spheroidal galaxies (dSphs) orbiting the Milky Way are widely regarded as systems supported by velocity dispersion against self-gravity, and as prime targets for the search for indirect dark matter (DM) signatures in the GeV-to-TeV $γ$-ray range owing to their lack of astrophysical $γ$-ray background. We present forecasts of the sensitivity of the forthcoming Cherenkov Telescope Array Observatory (CTAO) to annihilating or decaying DM signals in these targets. An original selection of candidates is performed from the current catalogue of known objects, including both classical and ultra-faint dSphs. For each, the expected DM content is derived using the most comprehensive photometric and spectroscopic data available, within a consistent framework of analysis. This approach enables the derivation of novel astrophysical factor profiles for indirect DM searches, which are compared with results from the literature. From an initial sample of 64 dSphs, eight promising targets are identified -- Draco I, Coma Berenices, Ursa Major II, Ursa Minor and Willman 1 in the North, Reticulum II, Sculptor and Sagittarius II in the South -- for which different DM density models yield consistent expectations, leading to robust predictions. CTAO is expected to provide the strongest limits above $\sim$10 TeV, reaching velocity-averaged annihilation cross sections of $\sim$5$\times$10$^{-25}$ cm$^3$ s$^{-1}$ and decay lifetimes up to $\sim$10$^{26}$ s for combined limits. The dominant uncertainties arise from the imprecise determination of the DM content, particularly for ultra-faint dSphs. Observation strategies are proposed that optimise either deep exposures of the best candidates or diversified target selections.

astro-ph.HE↗

Euclid preparation. Cosmology Likelihood for Observables in Euclid (CLOE). 6: Impact of systematic uncertainties on the cosmological analysis

Extracting cosmological information from the Euclid galaxy survey will require modelling numerous systematic effects during the inference process. This implies varying a large number of nuisance parameters, which have to be marginalised over before reporting the constraints on the cosmological parameters. This is a delicate process, especially with such a large parameter space, which could result in biased cosmological results. In this work, we study the impact of different choices for modelling systematic effects and prior distribution of nuisance parameters for the final Euclid Data Release, focusing on the 3$\times$2pt analysis for photometric probes and the galaxy power spectrum multipoles for the spectroscopic probes. We explore the effect of intrinsic alignments, linear galaxy bias, magnification bias, multiplicative cosmic shear bias and shifts in the redshift distribution for the photometric probes, as well as the purity of the spectroscopic sample. We find that intrinsic alignment modelling has the most severe impact with a bias up to $6\,σ$ on the Hubble constant $H_0$ if neglected, followed by mis-modelling of the redshift evolution of galaxy bias, yielding up to $1.5\,σ$ on the parameter $S_8\equivσ_8\sqrt{Ω_{\rm m} /0.3}$. Choosing a too optimistic prior for multiplicative bias can also result in biases of the order of $0.7\,σ$ on $S_8$. We also find that the precision on the estimate of the purity of the spectroscopic sample will be an important driver for the constraining power of the galaxy clustering full-shape analysis. These results will help prioritise efforts to improve the modelling and calibration of systematic effects in Euclid.

astro-ph.CO↗

Cosmology Likelihood for Observables in \Euclid (CLOE). 1. Theoretical recipe

As the statistical precision of cosmological measurements increases, the accuracy of the theoretical description of these measurements needs to increase correspondingly in order to infer the underlying cosmology that governs the Universe. To this end, we have created the Cosmology Likelihood for Observables in Euclid (CLOE), which is a novel cosmological parameter inference pipeline developed within the Euclid Consortium to translate measurements and covariances into cosmological parameter constraints. In this first in a series of six papers, we describe the theoretical recipe of this code for the Euclid primary probes. These probes are composed of the photometric 3x2pt observables of cosmic shear, galaxy-galaxy lensing, and galaxy clustering, along with spectroscopic galaxy clustering. We provide this description in both Fourier and configuration space for standard and extended summary statistics, including the wide range of systematic uncertainties that affect them. This includes systematic uncertainties such as intrinsic galaxy alignments, baryonic feedback, photometric and spectroscopic redshift uncertainties, shear calibration uncertainties, sample impurities, photometric and spectroscopic galaxy biases, as well as magnification bias. The theoretical descriptions are further able to accommodate both Gaussian and non-Gaussian likelihoods and extended cosmologies with non-zero curvature, massive neutrinos, evolving dark energy, and simple forms of modified gravity. These theoretical descriptions that underpin CLOE will form a crucial component in revealing the true nature of the Universe with next-generation cosmological surveys such as Euclid.

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Euclid preparation. Simulating thousands of Euclid spectroscopic skies

We present two extensive sets of 3500+1000 simulations of dark matter haloes on the past light cone, and two corresponding sets of simulated (`mock') galaxy catalogues that represent the Euclid spectroscopic sample. The simulations were produced with the latest version of the PINOCCHIO code, and provide the largest, public set of simulated skies. Mock galaxy catalogues were obtained by populating haloes with galaxies using an halo occupation distribution (HOD) model extracted from the Flagship galaxy catalogue provided by Euclid Collaboration. The Geppetto set of 3500 simulated skies was obtained by tiling a 1.2 Gpc/h box to cover a light-cone whose sky footprint is a circle of 30 deg radius, for an area of 2763 deg$^2$ and a minimum halo mass of $1.5\times10^{11}$ Msun/h. The relatively small box size makes this set unfit for measuring very large scales. The EuclidLargeBox set consists of 1000 simulations of 3.38 Gpc/h, with the same mass resolution and a footprint that covers half of the sky, excluding the Milky Way zone of avoidance. From this we produced a set of 1000 EuclidLargeMocks on the 30 deg radius footprint, whose comoving volume is fully contained in the simulation box. We validated the two sets of catalogues by analysing number densities, power spectra, and 2-point correlation functions, showing that the Flagship spectroscopic catalogue is consistent with being one of the realisations of the simulated sets, although we noticed small deviations limited to the quadrupole at k>0.2 h/Mpc. We show cosmological parameter inference from these catalogues and demonstrate that using one realisation of EuclidLargeMocks in place of the Flagship mock produces the same posteriors, to within the expected shift given by sample variance. These simulated skies will be used for the galaxy clustering analysis of Euclid's Data Release 1 (DR1).

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AMICO galaxy clusters in KiDS-1000: cosmological constraints and mass calibration from counts and weak lensing

We present the joint modelling of weak-lensing and count measurements of the galaxy clusters detected with the AMICO code, in the fourth data release of the Kilo Degree Survey (KiDS-1000). The analysed sample comprises about 8000 clusters, covering an effective area of 839 deg$^{2}$ and extending up to a redshift of $z = 0.8$. Stacked cluster weak-lensing and count measurements have been derived in bins of redshift and intrinsic richness, $λ^*$. Based on self-organising maps, we reconstructed the true redshift distributions of the background galaxy samples. We accounted for the systematic uncertainties arising from impurities in the background and cluster samples, biases in the cluster $z$ and $λ^*$, projection effects, halo orientation and miscentring, truncation of cluster halo mass distributions, matter correlated with cluster haloes, multiplicative shear bias, baryonic matter, geometric distortions in the lensing profiles, uncertainties in the theoretical halo mass function, and super-sample covariance. We also employed a blinding strategy based on perturbing the cluster sample completeness. The improved statistics and photometry compared to the previous KiDS data release, KiDS-DR3, have led to a halving of the uncertainties on $Ω_{\rm m}$ and $σ_8$, as we obtained $Ω_{\rm m}=0.22\pm0.02$ and $σ_8=0.86\pm0.03$. The constraint on $S_8 \equiv σ_8(Ω_{\rm m}/0.3)^{0.5}$, $S_8=0.74\pm0.03$, is in excellent agreement with recent cluster count and KiDS-1000 cosmic shear analyses, while it shows a $2.8σ$ tension with Planck cosmic microwave background results. The constraints on the $\logλ^*-\log M_{200}$ relation imply a mass precision of 8%, on average. In addition, the result on the intrinsic scatter of the $\logλ^*-\log M_{200}$ relation, $σ_{\rm intr}=0.05\pm0.02$, confirms that $λ^*$ is an excellent mass proxy.

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Euclid: A machine-learning search for dual and lensed AGN at sub-arcsec separations

Cosmological models of hierarchical structure formation predict the existence of a widespread population of dual accreting supermassive black holes (SMBHs) on kpc-scale separations, corresponding to projected distances < 0".8 at redshifts higher than 0.5. However, close companions to known active galactic nuclei (AGN) or quasars (QSOs) can also be multiple images of the object itself, strongly lensed by a foreground galaxy, as well as foreground stars in a chance superposition. Thanks to its large sky coverage, sensitivity, and high spatial resolution, Euclid offers a unique opportunity to obtain a large, homogeneous sample of dual/lensed AGN candidates with sub-arcsec projected separations. Here we present a machine learning approach, in particular a Convolutional Neural Network (CNN), to identify close companions to known QSOs down to separations of $\sim\,$0".15 comparable to the Euclid VIS point spread function (PSF). We studied the effectiveness of the CNN in identifying dual AGN and demonstrated that it outperforms traditional techniques. Applying our CNN to a sample of $\sim\,$6000 QSOs from the Q1 Euclid data release, we find a fraction of about 0.25% dual AGN candidates with separation $\sim\,$0".4 (corresponding to $\sim$3 kpc at z=1). Estimating the foreground contamination from stellar objects, we find that most of the pair candidates with separation higher than 0".5 are likely contaminants, while below this limit, contamination is expected to be less than 20%. For objects at higher separation (>0".5, i.e. 4 kpc at z=1), we performed PSF subtraction and used colour-colour diagrams to constrain their nature. We present a first set of dual/lensed AGN candidates detected in the Q1 Euclid data, providing a starting point for the analysis of future data releases.

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Euclid preparation. Predicting star-forming galaxy scaling relations with the spectral stacking code SpectraPyle

We introduce SpectraPyle, a versatile spectral stacking pipeline developed for the Euclid mission's NISP spectroscopic surveys, aimed at extracting faint emission lines and spectral features from large galaxy samples in the Wide and Deep Surveys. Designed for computational efficiency and flexible configuration, SpectraPyle supports the processing of extensive datasets critical to Euclid's non-cosmological science goals. We validate the pipeline using simulated spectra processed to match Euclid's expected final data quality. Stacking enables robust recovery of key emission lines, including Halpha, Hbeta, [O III], and [N II], below individual detection limits. However, the measurement of galaxy properties such as star formation rate, dust attenuation, and gas-phase metallicity are biased at stellar mass below log10(M*/Msol) ~ 9 due to the flux-limited nature of Euclid spectroscopic samples, which cannot be overcome by stacking. The SFR-stellar mass relation of the parent sample is recovered reliably only in the Deep survey for log10(M*/Msol) > 10, whereas the metallicity-mass relation is recovered more accurately over a wider mass range. These limitations are caused by the increased fraction of redshift measurement errors at lower masses and fluxes. We examine the impact of residual redshift contaminants that arises from misidentified emission lines and noise spikes, on stacked spectra. Even after stringent quality selections, low-level contamination (< 6%) has minimal impact on line fluxes due to the systematically weaker emission of contaminants. Percentile-based analysis of stacked spectra provides a sensitive diagnostic for detecting contamination via coherent spurious features at characteristic wavelengths. While our simulations include most instrumental effects, real Euclid data will require further refinement of contamination mitigation strategies.

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Euclid Quick Data Release (Q1). First Euclid statistical study of galaxy mergers and their connection to active galactic nuclei

Galaxy major mergers are a key pathway to trigger AGN. We present the first detection of major mergers in the Euclid Deep Fields and analyse their connection with AGN. We constructed a stellar-mass-complete ($M_*>10^{9.8}\,M_{\odot}$) sample of galaxies from the first quick data release (Q1), in the redshift range z=0.5-2. We selected AGN using X-ray data, optical spectroscopy, mid-infrared colours, and processing \IE observations with an image decomposition algorithm. We used CNNs trained on cosmological simulations to classify galaxies as mergers and non-mergers. We found a larger fraction of AGN in mergers compared to the non-merger controls for all AGN selections, with AGN excess factors ranging from 2 to 6. Likewise, a generally larger merger fraction ($f_{merg}$) is seen in active galaxies than in the non-active controls. We analysed $f_{merg}$ as a function of the AGN bolometric luminosity ($L_{bol}$) and the contribution of the point-source to the total galaxy light in the \IE-band ($f_{PSF}$) as a proxy for the relative AGN contribution fraction. We uncovered a rising $f_{merg}$, with increasing $f_{PSF}$ up to $f_{PSF}=0.55$, after which we observed a decreasing trend. We then derived the point-source luminosity ($L_{PSF}$) and showed that $f_{merg}$ monotonically increases as a function of $L_{PSF}$ at z<0.9, with $f_{merg}>$50% for $L_{PSF}>2\,10^{43}$ erg/s. At z>0.9, $f_{merg}$ rises as a function of $L_{PSF}$, though mergers do not dominate until $L_{PSF}=10^{45}$ erg/s. For X-ray and spectroscopic AGN, we computed $L_{bol}$, which has a positive correlation with $f_{merg}$ for X-ray AGN, while shows a less pronounced trend for spectroscopic AGN due to the smaller sample size. At $L_{bol}>10^{45}$ erg/s, AGN mostly reside in mergers. We concluded that mergers are strongly linked to the most powerful, dust-obscured AGN, associated with rapid supermassive black hole growth.

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Euclid: Methodology for derivation of IPC-corrected conversion gain of nonlinear CMOS APS

We introduce a fast method to measure the conversion gain in Complementary Metal-Oxide-Semiconductors (CMOS) Active Pixel Sensors (APS), which accounts for nonlinearity and interpixel capacitance (IPC). The standard 'mean-variance' method is biased because it assumes pixel values depend linearly on signal, and existing methods to correct for nonlinearity are still introducing significant biases. While current IPC correction methods are prohibitively slow for a per-pixel application, our new method uses separate measurements of the IPC kernel to make an almost instantaneous calculation of gain. Validated using test data from a flight detector from the ESA Euclid mission, the IPC correction recovers the results of slower methods within 0.1% accuracy. Meanwhile the nonlinearity correction ensures an estimation of the gain that is independent of signal, correcting a bias of more than 2.5% on gain estimation.

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Euclid Quick Data Release (Q1). Optical and near-infrared identification and classification of point-like X-ray selected sources

To better understand the role of active galactic nuclei (AGN) in galaxy evolution, it is crucial to achieve a complete and pure AGN census. X-ray surveys are key to this, but identifying their counterparts (CTPs) at other wavelengths remains challenging due to their larger positional uncertainties and limited availability of deeper, uniform ancillary data. Euclid is revolutionising this effort, offering extensive coverage of nearly the entire extragalactic sky, particularly in the near-infrared bands, where AGN are more easily detected. With the first Euclid Quick Data Release (Q1), we identifyed, classifyed, and determined the redshifts of Euclid CTPs to known point-like sources from major X-ray surveys, including XMM-Newton, Chandra, and eROSITA. Using Bayesian statistics, combined with machine learning (ML), we identify the CTPs to 11 286 X-ray sources from the three X-ray telescopes. For the large majority of 10 194 sources, the associations are unique, with the remaining $\sim$ 10% of multi-CTP cases equally split between XMM-Newton and eROSITA. ML is then used to distinguish between Galactic (8%) and extragalactic (92%) sources. We computed photo-zs using deep learning for the 8617 sources detected in the 10th data release of the DESI Legacy Survey, reaching an accuracy and a fraction of outliers of about 5%. Based on their X-ray luminosities, over 99% of CTPs identified as extragalactic are classified as AGN, most of which appear unobscured given their hardness ratios. With this paper, we release our catalogue, which includes identifiers, basic X-ray properties, the details of the associations, and additional features such as Galactic/extragalactic classifications and photometric/spectroscopic redshifts. We also provide probabilities for sub-selecting the sample based on purity and completeness, allowing users to tailor the sample according to their specific needs.

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Euclid Quick Data Release (Q1). First detections from the galaxy cluster workflow

The first survey data release by the Euclid mission covers approximately $63\,\mathrm{deg^2}$ 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 $0.2 \leq z \leq 1.5$. 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. 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.

astro-ph.CO↗

Euclid Quick Data Release (Q1). Exploring galaxy morphology across cosmic time through Sersic fits

We present the results of the single-component Sérsic profile fitting for the magnitude-limited sample of \IE$<23$ galaxies within the 63.1 deg$^2$ area of the Euclid Quick Data Release (Q1). The associated morphological catalogue includes two sets of structural parameters fitted using \texttt{SourceXtractor++}: one for VIS \IE images and one for a combination of three NISP images in \YE, \JE and \HE bands. We compare the resulting Sérsic parameters to other morphological measurements provided in the Q1 data release, and to the equivalent parameters based on higher-resolution \HST imaging. These comparisons confirm the consistency and the reliability of the fits to Q1 data. Our analysis of colour gradients shows that NISP profiles have systematically smaller effective radii ($R_{\rm e}$) and larger Sérsic indices ($n$) than in VIS. In addition, we highlight trends in NISP-to-VIS parameter ratios with both magnitude and $n_{\rm VIS}$. From the 2D bimodality of the $(u-r)$ colour-$\log(n)$ plane, we define a $(u-r)_{\rm lim}(n)$ that separates early- and late-type galaxies (ETGs and LTGs). We use the two subpopulations to examine the variations of $n$ across well-known scaling relations at $z<1$. ETGs display a steeper size--stellar mass relation than LTGs, indicating a difference in the main drivers of their mass assembly. Similarly, LTGs and ETGs occupy different parts of the stellar mass--star-formation rate plane, with ETGs at higher masses than LTGs, and further down below the Main Sequence of star-forming galaxies. This clear separation highlights the link known between the shutdown of star formation and morphological transformations in the Euclid imaging data set. In conclusion, our analysis demonstrates both the robustness of the Sérsic fits available in the Q1 morphological catalogue and the wealth of information they provide for studies of galaxy evolution with Euclid.

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Euclid: Early Release Observations -- Interplay between dwarf galaxies and their globular clusters in the Perseus galaxy cluster

We present an analysis of globular clusters (GCs) of dwarf galaxies in the Perseus galaxy cluster to explore the relationship between dwarf galaxy properties and their GCs. Our focus is on GC numbers ($N_{\rm GC}$) and GC half-number radii ($R_{\rm GC}$) around dwarf galaxies, and their relations with host galaxy stellar masses ($M_*$), central surface brightnesses ($μ_0$), and effective radii ($R_{\rm e}$). Interestingly, we find that at a given stellar mass, $R_{\rm GC}$ is almost independent of the host galaxy $μ_0$ and $R_{\rm e}$, while $R_{\rm GC}/R_{\rm e}$ depends on $μ_0$ and $R_{\rm e}$; lower surface brightness and diffuse dwarf galaxies show $R_{\rm GC}/R_{\rm e}\approx 1$ while higher surface brightness and compact dwarf galaxies show $R_{\rm GC}/R_{\rm e}\approx 1.5$-$2$. This means that for dwarf galaxies of similar stellar mass, the GCs have a similar median extent; however, their distribution is different from the field stars of their host. Additionally, low surface brightness and diffuse dwarf galaxies on average have a higher $N_{\rm GC}$ than high surface brightness and compact dwarf galaxies at any given stellar mass. We also find that UDGs (ultra-diffuse galaxies) and non-UDGs have similar $R_{\rm GC}$, while UDGs have smaller $R_{\rm GC}/R_{\rm e}$ (typically less than 1) and 3-4 times higher $N_{\rm GC}$ than non-UDGs. Examining nucleated and not-nucleated dwarf galaxies, we find that for $M_*>10^8M_{\odot}$, nucleated dwarf galaxies seem to have smaller $R_{\rm GC}$ and $R_{\rm GC}/R_{\rm e}$, with no significant differences between their $N_{\rm GC}$, except at $M_*<10^8M_{\odot}$ where the nucleated dwarf galaxies tend to have a higher $N_{\rm GC}$. Lastly, we explore the stellar-to-halo mass ratio (SHMR) of dwarf galaxies and conclude that the Perseus cluster dwarf galaxies follow the expected SHMR at $z=0$ extrapolated down to $M_*=10^6M_{\odot}$.

astro-ph.GA↗

Euclid preparation. LXXIV. Euclidised observations of Hubble Frontier Fields and CLASH galaxy clusters

We present HST2EUCLID, a novel Python code to generate Euclid realistic mock images in the $H_{\rm E}$, $J_{\rm E}$, $Y_{\rm E}$, and $I_{\rm E}$ photometric bands based on panchromatic Hubble Space Telescope observations. The software was used to create a simulated database of Euclid images for the 27 galaxy clusters observed during the Cluster Lensing And Supernova survey with Hubble (CLASH) and the Hubble Frontier Fields (HFF) program. Since the mock images were generated from real observations, they incorporate, by construction, all the complexity of the observed galaxy clusters. The simulated Euclid data of the galaxy cluster MACS J0416.1$-$2403 were then used to explore the possibility of developing strong lensing models based on the Euclid data. In this context, complementary photometric or spectroscopic follow-up campaigns are required to measure the redshifts of multiple images and cluster member galaxies. By Euclidising six parallel blank fields obtained during the HFF program, we provide an estimate of the number of galaxies detectable in Euclid images per ${\rm deg}^2$ per magnitude bin (number counts) and the distribution of the galaxy sizes. Finally, we present a preview of the Chandra Deep Field South that will be observed during the Euclid Deep Survey and two examples of galaxy-scale strong lensing systems residing in regions of the sky covered by the Euclid Wide Survey. The methodology developed in this work lends itself to several additional applications, as simulated Euclid fields based on HST (or JWST) imaging with extensive spectroscopic information can be used to validate the feasibility of legacy science cases or to train deep learning techniques in advance, thus preparing for a timely exploitation of the Euclid Survey data.

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