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M. Frailis

Publications and source records attributed to M. Frailis.

At least 145 records · Page 8Linked to original sources

Euclid: Relativistic effects in the dipole of the 2-point correlation function

Gravitational redshift and Doppler effects give rise to an antisymmetric component of the galaxy correlation function when cross-correlating two galaxy populations or two different tracers. In this paper, we assess the detectability of these effects in the Euclid spectroscopic galaxy survey. We model the impact of gravitational redshift on the observed redshift of galaxies in the Flagship mock catalogue using a Navarro-Frenk-White profile for the host haloes. We isolate these relativistic effects, largely subdominant in the standard analysis, by splitting the galaxy catalogue into two populations of faint and bright objects and estimating the dipole of their cross-correlation in four redshift bins. In the simulated catalogue, we detect the dipole signal on scales below $30\,h^{-1}{\rm Mpc}$, with detection significances of $4\,σ$ and $3\,σ$ in the two lowest redshift bins, respectively. At higher redshifts, the detection significance drops below $2\,σ$. Overall, we estimate the total detection significance in the Euclid spectroscopic sample to be approximately $6\,σ$. We find that on small scales, the major contribution to the signal comes from the nonlinear gravitational potential. Our study on the Flagship mock catalogue shows that this observable can be detected in Euclid Data Release 2 and beyond.

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Euclid Quick Data Release (Q1): From images to multiwavelength catalogues: the Euclid MERge Processing Function

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 $14\,000~\text{deg}^2$ with two instruments, the Visible Camera (VIS) and the Near IR Spectrometer and Photometer (NISP) down to $I_{\rm E} = 24.5~\text{mag}$ ($10\, σ$) in the Euclid Wide Survey. Ground-based imaging data in the \textit{ugriz} bands complement the \Euclid data to enable photo-$z$ determination and VIS PSF modeling for week lensing analysis. Euclid investigates the distance-redshift relation and the evolution of cosmic structures by measuring shapes and redshifts of galaxies and clusters of galaxies out to $z\sim 2$. 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 MER Processing Function (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.

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Euclid preparation. Constraining parameterised models of modifications of gravity with the spectroscopic and photometric primary probes

The Euclid mission has the potential to understand the fundamental physical nature of late-time cosmic acceleration and, as such, of deviations from the standard cosmological model, LCDM. In this paper, we focus on model-independent methods to modify the evolution of scalar perturbations at linear scales. We consider two approaches: the first is based on the two phenomenological modified gravity (PMG) parameters, $μ_{\rm mg}$ and $Σ_{\rm mg}$, which are phenomenologically connected to the clustering of matter and weak lensing, respectively; and the second is the effective field theory (EFT) of dark energy and modified gravity, which we use to parameterise the braiding function, $α_{\rm B}$, which defines the mixing between the metric and the dark energy field. We discuss the predictions from spectroscopic and photometric primary probes by Euclid on the cosmological parameters and a given set of additional parameters featuring the PMG and EFT models. We use the Fisher matrix method applied to spectroscopic galaxy clustering (GCsp), weak lensing (WL), photometric galaxy clustering (GCph), and cross-correlation (XC) between GCph and WL. For the modelling of photometric predictions on nonlinear scales, we use the halo model to cover two limits for the screening mechanism: the unscreened (US) case, for which the screening mechanism is not present; and the super-screened (SS) case, which assumes strong screening. We also assume scale cuts to account for our uncertainties in the modelling of nonlinear perturbation evolution. We choose a time-dependent form for $\{μ_{\rm mg},Σ_{\rm mg}\}$, with two fiducial sets of values for the corresponding model parameters at the present time, $\{\barμ_0,\barΣ_0\}$, and two forms for $α_{\rm B}$, with one fiducial set of values for each of the model parameters, $α_{\rm B,0}$ and $\{α_{\rm B,0},m\}$. (Abridged)

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Performance of the image persistence model for Euclid infrared detectors

Large-format infrared detectors are at the heart of major ground and space-based astronomical instruments, and the HgCdTe HxRG is the most widely used. The Near Infrared Spectrometer and Photometer (NISP) of the ESA's Euclid mission launched in July 2023 hosts 16 H2RG detectors in the focal plane. Their performance relies heavily on the effect of image persistence, which results in residual images that can remain in the detector for a long time contaminating any subsequent observations. Deriving a precise model of image persistence is challenging due to the sensitivity of this effect to observation history going back hours or even days. Nevertheless, persistence removal is a critical part of image processing because it limits the accuracy of the derived cosmological parameters. We will present the empirical model of image persistence derived from ground characterization data, adapted to the Euclid observation sequence and compared with the data obtained during the in-orbit calibrations of the satellite.

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Euclid: Early Release Observations of ram-pressure stripping in the Perseus cluster. Detection of parsec scale star formation with in the low surface brightness stripped tails of UGC 2665 and MCG +07-07-070

Euclid is delivering optical and near-infrared imaging data over 14,000 deg$^2$ on the sky at spatial resolution and surface brightness levels that can be used to understand the morphological transformation of galaxies within groups and clusters. Using the Early Release Observations (ERO) of the Perseus cluster, we demonstrate the capability offered by Euclid in studying the nature of perturbations for galaxies in clusters. Filamentary structures are observed along the discs of two spiral galaxies with no extended diffuse emission expected from tidal interactions at surface brightness levels of $\sim$ $30\,{\rm mag}\,{\rm arcsec}^{-2}$. The detected features exhibit a good correspondence in morphology between optical and near-infrared wavelengths, with a surface brightness of $\sim$ $25\,{\rm mag}\,{\rm arcsec}^{-2}$, and the knots within the features have sizes of $\sim$ 100 pc, as observed through $I_E$ imaging. Using the Euclid, CFHT, UVIT, and LOFAR $144\,{\rm MHz}$ radio continuum observations, we conduct a detailed analysis to understand the origin of the detected features. We constructed the \textit{Euclid} $I_E-Y_E$, $Y_E-H_E$, and CFHT $u - r$, $g - i$ colour-colour plane and showed that these features contain recent star formation events, which are also indicated by their H$α$ and NUV emissions. Euclid colours alone are insufficient for studying stellar population ages in unresolved star-forming regions, which require multi-wavelength optical imaging data. The morphological shape, orientation, and mean age of the stellar population, combined with the presence of extended radio continuum cometary tails can be consistently explained if these features have been formed during a recent ram-pressure stripping event. This result further confirms the exceptional qualities of Euclid in the study of galaxy evolution in dense environments.

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Euclid preparation LXXI. Simulations and nonlinearities beyond $\mathsfΛ$CDM. 3. Constraints on $f(R)$ models from the photometric primary probes

We study the constraint on $f(R)$ gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the Hu-Sawicki $f(R)$ gravity model, we consider four different predictions for the ratio between the power spectrum in $f(R)$ and that in $Λ$CDM: a fitting formula, the halo model reaction approach, ReACT and two emulators based on dark matter only $N$-body simulations, FORGE and e-Mantis. These predictions are added to the MontePython implementation to predict the angular power spectra for weak lensing (WL), photometric galaxy clustering and their cross-correlation. By running Markov Chain Monte Carlo, we compare constraints on parameters and investigate the bias of the recovered $f(R)$ parameter if the data are created by a different model. For the pessimistic setting of WL, one dimensional bias for the $f(R)$ parameter, $\log_{10}|f_{R0}|$, is found to be $0.5 σ$ when FORGE is used to create the synthetic data with $\log_{10}|f_{R0}| =-5.301$ and fitted by e-Mantis. The impact of baryonic physics on WL is studied by using a baryonification emulator BCemu. For the optimistic setting, the $f(R)$ parameter and two main baryon parameters are well constrained despite the degeneracies among these parameters. However, the difference in the nonlinear dark matter prediction can be compensated by the adjustment of baryon parameters, and the one-dimensional marginalised constraint on $\log_{10}|f_{R0}|$ is biased. This bias can be avoided in the pessimistic setting at the expense of weaker constraints. For the pessimistic setting, using the $Λ$CDM synthetic data for WL, we obtain the prior-independent upper limit of $\log_{10}|f_{R0}|< -5.6$. Finally, we implement a method to include theoretical errors to avoid the bias.

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Euclid Quick Data Release (Q1). A first view of the star-forming main sequence in the Euclid Deep Fields

The star-forming main sequence (SFMS) is a tight relation observed between stellar masses and star formation rates (SFR) in a population of galaxies. This relation is observed at different redshifts, in various morphological, and environmental domains, and is key to understanding the underlying relations between a galaxy budget of cold gas and its stellar content. Euclid Quick Data Release 1 (Q1) gives us the opportunity to investigate this fundamental relation in galaxy formation and evolution. We complement the Euclid release with public IRAC observations of the Euclid Deep Fields, improving the quality of recovered photometric redshifts, stellar masses, and SFRs, as is shown both with simulations and a comparison with available spectroscopic redshifts. From Q1 data alone, we recover more than $\sim 30\,\mathrm{k}$ galaxies with $\log_{10} (M_\ast/M_\odot) > 11$, giving a precise constraint of the SFMS at the high-mass end. We investigated the SFMS, in a redshift interval between $0.2$ and $3.0$, comparing our results with the existing literature and fitting them with a parameterisation taking into account the presence of a bending of the relation at the high-mass end, depending on the bending mass, $M_0$. We find good agreement with previous results in terms of $M_0$ values, and an increasing trend for the relation scatter at higher stellar masses. We also investigate the distribution of physical (e.g. dust absorption, $A_V$, and formation age) and morphological properties (e.g., Sérsic index and radius) in the SFR--stellar mass plane, and their relation with the SFMS. These results highlight the potential of Euclid in studying the fundamental scaling relations that regulate galaxy formation and evolution in anticipation of the forthcoming Data Release 1.

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Euclid preparation: TBD. Cosmic Dawn Survey: evolution of the galaxy stellar mass function across 0.2<z<6.5 measured over 10 square degrees

The Cosmic Dawn Survey Pre-launch (PL) catalogues cover an effective 10.13 deg$^{2}$ area with uniform deep Spitzer/IRAC data ($m\sim25$ mag, 5$σ$), the largest area covered to these depths in the infrared. These data are used to gain new insight into the growth of stellar mass across cosmic history by characterising the evolution of the galaxy stellar mass function (GSMF) through $0.2 < z \leq 6.5$. The total volume (0.62 Gpc$^{3}$) represents a tenfold increase compared to previous works that have explored $z > 3$ and significantly reduces cosmic variance, yielding strong constraints on the abundance of massive galaxies. Results are generally consistent with the literature but now provide firm estimates of number density where only upper limits were previously available. Contrasting the GSMF with the dark matter halo mass function suggests that massive galaxies ($M \gtrsim10^{11}$ M$_{\odot}$) at $z > 3.5$ required integrated star-formation efficiencies of $M/(M_{\rm h}f_{\rm b}) \gtrsim$ 0.25--0.5, in excess of the commonly-held view of ``universal peak efficiency" from studies on the stellar-to-halo mass relation (SHMR). Such increased efficiencies imply an evolving peak in the SHMR at $z > 3.5$ which can be maintained if feedback mechanisms from active galactic nuclei and stellar processes are ineffective at early times. In addition, a significant fraction of the most massive quiescent galaxies are observed to be in place already by $z\sim 2.5$--3. The apparent lack in change of their number density by $z\sim 0.2$ is consistent with relatively little mass growth from mergers. Utilising the unique volume, evidence for an environmental dependence of the galaxy stellar mass function is found all the way through $z\sim 3.5$ for the first time, though a more careful characterisation of the density field is ultimately required for confirmation.

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Euclid preparation. Estimating galaxy physical properties using CatBoost chained regressors with attention

Euclid will image ~14000 deg^2 of the extragalactic sky at visible and NIR wavelengths, providing a dataset of unprecedented size and richness that will facilitate a multitude of studies into the evolution of galaxies. In the vast majority of cases the main source of information will come from broad-band images and data products thereof. Therefore, there is a pressing need to identify or develop scalable yet reliable methodologies to estimate the redshift and physical properties of galaxies using broad-band photometry from Euclid, optionally including ground-based optical photometry also. To address this need, we present a novel method to estimate the redshift, stellar mass, star-formation rate, specific star-formation rate, E(B-V), and age of galaxies, using mock Euclid and ground-based photometry. The main novelty of our property-estimation pipeline is its use of the CatBoost implementation of gradient-boosted regression-trees, together with chained regression and an intelligent, automatic optimization of the training data. The pipeline also includes a computationally-efficient method to estimate prediction uncertainties, and, in the absence of ground-truth labels, provides accurate predictions for metrics of model performance up to z~2. We apply our pipeline to several datasets consisting of mock Euclid broad-band photometry and mock ground-based ugriz photometry, to evaluate the performance of our methodology for estimating the redshift and physical properties of galaxies detected in the Euclid Wide Survey. The quality of our photometric redshift and physical property estimates are highly competitive overall, validating our modeling approach. We find that the inclusion of ground-based optical photometry significantly improves the quality of the property estimation, highlighting the importance of combining Euclid data with ancillary ground-based optical data. (Abridged)

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Euclid preparation. LXVIII. Extracting physical parameters from galaxies with machine learning

The Euclid mission is generating a vast amount of imaging data in four broadband filters at high angular resolution. This will allow the detailed study of mass, metallicity, and stellar populations across galaxies, which will constrain their formation and evolutionary pathways. Transforming the Euclid imaging for large samples of galaxies into maps of physical parameters in an efficient and reliable manner is an outstanding challenge. We investigate the power and reliability of machine learning techniques to extract the distribution of physical parameters within well-resolved galaxies. We focus on estimating stellar mass surface density, mass-averaged stellar metallicity and age. We generate noise-free, synthetic high-resolution imaging data in the Euclid photometric bands for a set of 1154 galaxies from the TNG50 cosmological simulation. The images are generated with the SKIRT radiative transfer code, taking into account the complex 3D distribution of stellar populations and interstellar dust attenuation. We use a machine learning framework to map the idealised mock observational data to the physical parameters on a pixel-by-pixel basis. We find that stellar mass surface density can be accurately recovered with a $\leq 0.130 {\rm \,dex}$ scatter. Conversely, stellar metallicity and age estimates are, as expected, less robust, but still contain significant information which originates from underlying correlations at a sub-kpc scale between stellar mass surface density and stellar population properties.

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Euclid Quick Data Release (Q1) Ultracool dwarfs in the Euclid Deep Field North

Ultracool dwarfs (UCDs) encompass the lowest mass stars and brown dwarfs, defining the stellar substellar boundary. They have significant potential for advancing the understanding of substellar physics; however, these objects are challenging to detect due to their low luminosity. The wide coverage and deep sensitivity of the Euclid survey will increase the number of confirmed and well characterised UCDs by several orders of magnitude. In this study, we take advantage of the Euclid Quick Data Release (Q1) and in particular we look in detail at the known and new UCDs in the Euclid Deep Field North (22.9 deg2 down to JE = 24.5 mag), to understand the advantages of using the slitless Euclid spectroscopy. We compile a comparison sample of known UCDs and use their spectra to demonstrate the capability of Euclid to derive spectral types using a template matching method. This method is then applied to the spectra of the newly identified candidates. We confirm that 33 of these candidates are new UCDs, with spectral types ranging from M7 to T1 and JE = 17 to 21 mag. We look at their locus in colour colour diagrams and compare them with the expected colours of QSOs. A machine readable catalogue is provided for further study, containing both the comparison sample and the newly identified UCDs, along with their spectral classifications where the Q1 spectra quality allows for confident determination

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Euclid preparation LXIII. Simulations and nonlinearities beyond $Λ$CDM. 2. Results from non-standard simulations

The Euclid mission will measure cosmological parameters with unprecedented precision. To distinguish between cosmological models, it is essential to generate realistic mock observables from cosmological simulations that were run in both the standard $Λ$-cold-dark-matter ($Λ$CDM) paradigm and in many non-standard models beyond $Λ$CDM. We present the scientific results from a suite of cosmological N-body simulations using non-standard models including dynamical dark energy, k-essence, interacting dark energy, modified gravity, massive neutrinos, and primordial non-Gaussianities. We investigate how these models affect the large-scale-structure formation and evolution in addition to providing synthetic observables that can be used to test and constrain these models with Euclid data. We developed a custom pipeline based on the Rockstar halo finder and the nbodykit large-scale structure toolkit to analyse the particle output of non-standard simulations and generate mock observables such as halo and void catalogues, mass density fields, and power spectra in a consistent way. We compare these observables with those from the standard $Λ$CDM model and quantify the deviations. We find that non-standard cosmological models can leave significant imprints on the synthetic observables that we have generated. Our results demonstrate that non-standard cosmological N-body simulations provide valuable insights into the physics of dark energy and dark matter, which is essential to maximising the scientific return of Euclid.

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Euclid preparation. LXVII. Deep learning true galaxy morphologies for weak lensing shear bias calibration

To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double Sérsic profile, neglecting the influence of galaxy substructures and morphologies deviating from such a simplified parametric characterization. While this approximation may be sufficient for previous data sets, the stringent cosmic shear calibration requirements and the high quality of the data in the upcoming Euclid survey demand a consideration of the effects that realistic galaxy substructures have on shear measurement biases. Here we present a novel deep learning-based method to create such simulated galaxies directly from HST data. We first build and validate a convolutional neural network based on the wavelet scattering transform to learn noise-free representations independent of the point-spread function of HST galaxy images that can be injected into simulations of images from Euclid's optical instrument VIS without introducing noise correlations during PSF convolution or shearing. Then, we demonstrate the generation of new galaxy images by sampling from the model randomly and conditionally. Next, we quantify the cosmic shear bias from complex galaxy shapes in Euclid-like simulations by comparing the shear measurement biases between a sample of model objects and their best-fit double-Sérsic counterparts. Using the KSB shape measurement algorithm, we find a multiplicative bias difference between these branches with realistic morphologies and parametric profiles on the order of $6.9\times 10^{-3}$ for a realistic magnitude-Sérsic index distribution. Moreover, we find clear detection bias differences between full image scenes simulated with parametric and realistic galaxies, leading to a bias difference of $4.0\times 10^{-3}$ independent of the shape measurement method. This makes it relevant for stage IV weak lensing surveys such as Euclid.

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Euclid preparation LXX. Forecasting detection limits for intracluster light in the Euclid Wide Survey

The intracluster light (ICL) permeating galaxy clusters is a tracer of the cluster's assembly history, and potentially a tracer of their dark matter structure. In this work we explore the capability of the Euclid Wide Survey to detect ICL using H-band mock images. We simulate clusters across a range of redshifts (0.3-1.8) and halo masses ($10^{13.9}$-$10^{15.0}$ M$_\odot$), using an observationally motivated model of the ICL. We identify a 50-200 kpc circular annulus around the brightest cluster galaxy (BCG) in which the signal-to-noise ratio (S/N) of the ICL is maximised and use the S/N within this aperture as our figure of merit for ICL detection. We compare three state-of-the-art methods for ICL detection, and find that a method that performs simple aperture photometry after high-surface brightness source masking is able to detect ICL with minimal bias for clusters more massive than $10^{14.2}$ M$_\odot$. The S/N of the ICL detection is primarily limited by the redshift of the cluster, driven by cosmological dimming, rather than the mass of the cluster. Assuming the ICL in each cluster contains 15% of the stellar light, we forecast that Euclid will be able to measure the presence of ICL in up to $\sim80000$ clusters of $>10^{14.2}$ M$_\odot$ between $z=0.3$ and 1.5 with a S/N$>3$. Half of these clusters will reside below $z=0.75$ and the majority of those below $z=0.6$ will be detected with a S/N $>20$. A few thousand clusters at $1.3 10^{14.7}$ M$_\odot$. Euclid will detect the ICL at more than 500 kpc distance from the BCG, up to $z=0.7$, in several hundred of these massive clusters over its large survey volume.

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Euclid Quick Data Release (Q1). Combined Euclid and Spitzer galaxy density catalogues at $z>$ 1.3 and detection of significant Euclid passive galaxy overdensities in Spitzer overdense regions

Euclid will detect tens of thousands of clusters and protoclusters at $z$>1.3. With a total coverage of 63.1deg$^2$, the Euclid Quick Data Release 1 (Q1) is large enough to detect tens of clusters and hundreds of protoclusters at these early epochs. The Q1 photometric redshift catalogue enables us to detect clusters out to $z$ < 1.5; however, infrared imaging from Spitzer extends this limit to higher redshifts by using high local projected densities of Spitzer-selected galaxies as signposts for cluster and protocluster candidates. We use Spitzer imaging of the Euclid Deep Fields (EDFs) to derive densities for a sample of Spitzer-selected galaxies at redshifts $z$ > 1.3, building Spitzer IRAC1 and IRAC2 photometric catalogues that are 95% complete at a magnitude limit of IRAC2=22.2, 22.6, and 22.8 for the EDF-S, EDF-F, and EDF-N, respectively. We apply two complementary methods to calculate galaxy densities: (1) aperture and surface density; and (2) the Nth-nearest-neighbour method. When considering a sample selected at a magnitude limit of IRAC2 < 22.2, at which all three EDFs are 95% complete, our surface density distributions are consistent among the three EDFs and with the SpUDS blank field survey. We also considered a deeper sample (IRAC2 < 22.8), finding that 2% and 3% of the surface densities in the North and Fornax fields are 3$σ$ higher than the average field distribution and similar to densities found in the CARLA cluster survey. Our surface densities are also consistent with predictions from the GAEA semi-analytical model. Using combined Euclid and ground-based i-band photometry we show that our highest Spitzer-selected galaxy overdense regions, found at $z$~1.5, also host high densities of passive galaxies. This means that we measure densities consistent with those found in clusters and protoclusters at $z$>1.3.

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Euclid: Star clusters in IC 342, NGC 2403, and Holmberg II

We examine the star cluster populations in the three nearby galaxies IC 342, NGC 2403, and Holmberg II, observed as part of the Euclid Early Release Observations programme. Our main focus is on old globular clusters (GCs), for which the wide field-of-view and excellent image quality of Euclid offer substantial advantages over previous work. For IC 342 this is the first study of stellar clusters other than its nuclear cluster. After selection based on size and magnitude criteria, followed by visual inspection, we identify 111 old (> 1 Gyr) GC candidates in IC 342, 50 in NGC 2403 (of which 15 were previously known), and 7 in Holmberg II. In addition, a number of younger and/or intermediate-age candidates are identified. The colour distributions of GC candidates in the two larger galaxies show hints of bimodality with peaks at IE-HE = 0.36 and 0.79 (IC 342) and IE-HE = 0.36 and 0.80 (NGC 2403), corresponding to metallicities of [Fe/H]=-1.5 and [Fe/H]=-0.5, similar to those of the metal-poor and metal-rich GC subpopulations in the Milky Way. The luminosity functions of our GC candidates exhibit an excess of relatively faint objects, relative to a canonical, approximately Gaussian GC luminosity function (GCLF). The excess objects may be similar to those previously identified in other galaxies. The specific frequency of classical old GCs in IC 342, as determined based on the brighter half of the GCLF, appears to be unusually low with SN=0.2-0.3. The combined luminosity function of young and intermediate-age clusters in all three galaxies is consistent with a power-law distribution, dN/dL ~ L^(-2.3+/-0.1) and the total numbers of young clusters brighter than M(IE)=-8 in NGC 2403 and Holmberg II are comparable with those found in their Local Group counterparts, that is, M33 and the Small Magellanic Cloud, respectively.

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Euclid Quick Data Release (Q1) -- Data release overview

The first Euclid Quick Data Release, Q1, comprises 63.1 sq deg of the Euclid Deep Fields (EDFs) to nominal wide-survey depth. It encompasses visible and near-infrared space-based imaging and spectroscopic data, ground-based photometry in the u, g, r, i and z bands, as well as corresponding masks. Overall, Q1 contains about 30 million objects in three areas near the ecliptic poles around the EDF-North and EDF-South, as well as the EDF-Fornax field in the constellation of the same name. The purpose of this data release -- and its associated technical papers -- is twofold. First, it is meant to inform the community of the enormous potential of the Euclid survey data, to describe what is contained in these data, and to help prepare expectations for the forthcoming first major data release DR1. Second, it enables a wide range of initial scientific projects with wide-survey Euclid data, ranging from the early Universe to the Solar System. The Q1 data were processed with early versions of the processing pipelines, which already demonstrate good performance, with numerous improvements in implementation compared to pre-launch development. In this paper, we describe the sky areas released in Q1, the observations, a top-level view of the data processing of Euclid and associated external data, the Q1 photometric masks, and how to access the data. We also give an overview of initial scientific results obtained using the Q1 data set by Euclid Consortium scientists, and conclude with important caveats when using the data. As a complementary product, Q1 also contains observations of a star-forming area in Lynd's Dark Nebula 1641 in the Orion~A Cloud, observed for technical purposes during Euclid's performance-verification phase. This is a unique target, of a type not commonly found in Euclid's nominal sky survey.

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Euclid Quick Data Release (Q1). NIR processing and data products

This paper describes the near-infrared processing function (NIR PF) that processes near-infrared images from the Near-Infrared Spectrometer and Photometer (NISP) instrument onboard the Euclid satellite. NIR PF consists of three main components: (i) a common pre-processing stage for both photometric (NIR) and spectroscopic (SIR) data to remove instrumental effects; (ii) astrometric and photometric calibration of NIR data, along with catalogue extraction; and (iii) resampling and stacking. The necessary calibration products are generated using dedicated pipelines that process observations from both the early performance verification (PV) phase in 2023 and the nominal survey operations. After outlining the pipeline's structure and algorithms, we demonstrate its application to Euclid Q1 images. For Q1, we achieve an astrometric accuracy of 9-15 mas, a relative photometric accuracy of 5 mmag, and an absolute flux calibration limited by the 1% uncertainty of the Hubble Space Telescope (HST) CALSPEC database. We characterise the point-spread function (PSF) that we find very stable across the focal plane, and we discuss current limitations of NIR PF that will be improved upon for future data releases.

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