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H. Dole

Publications and source records attributed to H. Dole.

At least 91 records · Page 5Linked to original sources

Euclid: Galaxy SED reconstruction in the PHZ processing function: impact on the PSF and the role of medium-band filters

Weak lensing surveys require accurate correction for the point spread function (PSF) when measuring galaxy shapes. For a diffraction-limited PSF, as arises in space-based missions, this correction depends on each galaxy SED. In the Euclid mission, galaxy SED reconstruction, a tasks of the photometric-redshift processing function (PHZ PF), relies on broad- and medium-band ancillary photometry. The limited wavelength sampling of the Euclid VIS passband and signal-to-noise ratio may affect the reconstruction accuracy and translate into biases in the weak lensing measurements. In this study, we present the methodology, which is employed in the Euclid PHZ PF, for reconstructing galaxy SEDs at 55 wavelengths, sampling the VIS passband every 10 nm, and we assess whether it fulfils the accuracy requirements imposed on the Euclid PSF model. We employ both physics- and data-driven methods, focusing on a new approach of template-based flux correction and Gaussian processes, and we introduce an SED metric whose bias propagates into PSF quadrupole moment errors. Our findings demonstrate that Gaussian processes and template fitting meet the requirements only in specific, but complementary, redshift intervals. We therefore propose a hybrid approach, which leverages both methods. This solution proves to be effective in meeting the Euclid accuracy requirements for most of the redshift range of the survey. Finally, we investigate the impact on the SED reconstruction of a new set of 16 evenly-spaced medium-band filters for the Subaru telescope, providing quasi-spectroscopic coverage of the VIS passband. This study shows promising results, ensuring accurate SED reconstruction and meeting the mission PSF requirements. This work thus provides not only the methodological foundation of galaxy SED reconstruction in the Euclid PHZ PF, but also a roadmap for future improvements using a new medium-band survey.

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Euclid preparation. 3D reconstruction of the cosmic web with simulated Euclid Deep spectroscopic samples

The ongoing Euclid mission aims to measure spectroscopic redshifts for approximately two million galaxies using the H $α$ line emission detected in near-infrared slitless spectroscopic data from the Euclid Deep Fields (EDFs). These measurements will reach a flux limit of $5\times 10^{-17}\,{\rm erg}\,{\rm cm}^{-2}\,{\rm s}^{-1}$ in the redshift range $0.4<z<1.8$, opening the door to numerous investigations involving galaxy evolution, extending well beyond the mission's core objectives. The achieved H $α$ luminosity depth will lead to a sufficiently high sampling, enabling the reconstruction of the large-scale galaxy environment. We assess the quality of the reconstruction of the galaxy cosmic web environment with the expected spectroscopic dataset in EDFs. The analysis is carried out on the Flagship and GAEA galaxy mock catalogues. The quality of the reconstruction is first evaluated using geometrical and topological statistics measured on the cosmic web, namely the length of filaments, the area of walls, the volume of voids, and its connectivity and multiplicity. We then quantify how accurately gradients in galaxy properties with distance from filaments can be recovered. As expected, the small-scale redshift-space distortions, have a strong impact on filament lengths and connectivity, but can be mitigated by compressing galaxy groups before skeleton extraction. The cosmic web reconstruction is biased when relying solely on H $α$ emitters. This limitation can be mitigated by applying stellar mass weighting during the reconstruction. However, this approach introduces non-trivial biases that need to be accounted for when comparing to theoretical predictions. Redshift uncertainties pose the greatest challenge in recovering the expected dependence of galaxy properties, though the well-established stellar mass transverse gradients towards filaments can still be observed.

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Euclid preparation. Calibrated intrinsic galaxy alignments in the Euclid Flagship simulation

Intrinsic alignments of galaxies are potentially a major contaminant of cosmological analyses of weak gravitational lensing. We construct a semi-analytic model of galaxy ellipticities and alignments in the \Euclid Flagship simulation to predict this contamination in Euclid's weak lensing observations. Galaxy shapes and orientations are determined by the corresponding properties of the host haloes in the underlying $N$-body simulation, as well as the relative positions of galaxies within their halo. Alignment strengths are moderated via stochastic misalignments, separately for central and satellite galaxies and conditional on the galaxy's redshift, luminosity, and rest-frame colour. The resulting model is calibrated against galaxy ellipticity statistics from the COSMOS Survey, selected alignment measurements based on Sloan Digital Sky Survey samples, and galaxy orientations extracted from the Horizon-AGN hydrodynamic simulation at redshift $z=1$. The best-fit model has a total of 12 alignment parameters and generally reproduces the calibration data sets well within the $1σ$ statistical uncertainties of the observations and the \flagship simulation, with notable exceptions for the most luminous sub-samples on small physical scales. The statistical power of the calibration data and the volume of the single \flagship realisation are still too small to provide informative prior ranges for intrinsic alignment amplitudes in relevant galaxy samples. As a first application, we predict that \Euclid end-of-mission tomographic weak gravitational lensing two-point statistics are modified by up to order $10\,\%$ due to intrinsic alignments.

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Euclid preparation. Galaxy 2-point correlation function modelling in redshift space

The Euclid satellite will measure spectroscopic redshifts for tens of millions of emission-line galaxies. In the context of Stage-IV surveys, the 3-dimensional clustering of galaxies plays a key role in providing cosmological constraints. In this paper, we conduct a model comparison for the multipole moments of the galaxy 2-point correlation function (2PCF) in redshift space. We test state-of-the-art models, in particular the effective field theory of large-scale structure (EFT), one based on the velocity difference generating function (VDG$_{\infty}$), and different variants of Lagrangian perturbation theory (LPT) models, such as convolutional LPT (CLPT) and its effective-field-theory extension (CLEFT). We analyse the first three even multipoles of the 2PCF in the Flagship 1 simulation, which consists of four snapshots at $z\in\{0.9,1.2,1.5,1.8\}$. We study both template-fitting and full-shape approaches and find that with the template-fitting approach, only the VDG$_{\infty}$ model is able to reach a minimum fitting scale of $s_{\rm min}=20\,h^{-1}\,{\rm Mpc}$ at $z=0.9$ without biasing the recovered parameters. Indeed, the EFT model becomes inaccurate already at $s_{\rm min}=30\,h^{-1}\,{\rm Mpc}$. Conversely, in the full-shape analysis, the CLEFT and VDG$_{\infty}$ models perform similarly well, but only the CLEFT model can reach $s_{\rm min}=20\,h^{-1}\,{\rm Mpc}$ while the VDG$_{\infty}$ model is unbiased down to $s_{\rm min}=25\,h^{-1}\,{\rm Mpc}$ at the lowest redshift. Overall, in order to achieve the accuracy required by Euclid, non-perturbative modelling such as in the VDG$_{\infty}$ or CLEFT models should be considered. At $z=1.8$, the CLPT model is sufficient to describe the data with high figure of merit. This comparison selects baseline models that perform best in ideal conditions and sets the stage for an optimal analysis of Euclid data in configuration space.

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Euclid preparation. LXXXV. Toward a DR1 application of higher-order weak lensing statistics

This is the second paper in the HOWLS (higher-order weak lensing statistics) series exploring the usage of non-Gaussian statistics for cosmology inference within Euclid. With respect to our first paper, we develop a full tomographic analysis based on realistic photometric redshifts that allows us to derive Fisher forecasts in the ($σ_8$, $w_0$) plane for a Euclid-like data release 1 (DR1) setup. We find that the five higher-order statistics (HOS) that satisfy the Gaussian likelihood assumption of the Fisher formalism (one-point probability distribution function, $\ell$1-norm, peak counts, Minkowski functionals, and Betti numbers) each outperform the shear two-point correlation functions by a factor of $2.5$ on the $w_0$ forecasts, with only marginal improvement when used in combination with two-point estimators, suggesting that every HOS is able to retrieve both the non-Gaussian and Gaussian information of the matter density field. The similar performance of the different estimators is explained by a homogeneous use of multi-scale and tomographic information, optimized to lower computational costs. These results hold for the three mass mapping techniques of the Euclid pipeline, aperture mass, Kaiser--Squires, and Kaiser--Squires plus, and they are unaffected by the application of realistic star masks. Finally, we explored the use of HOS with the Bernardeau--Nishimichi--Taruya (BNT) nulling scheme approach, finding promising results toward applying physical scale cuts to HOS.

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Euclid: Improving redshift distribution reconstruction using a deep-to-wide transfer function

The Euclid mission seeks to understand the Universe expansion history and the nature of dark energy, which requires a very accurate estimate of redshift distribution. Achieving this accuracy relies on reference samples with spectroscopic redshifts, together with a procedure to match them to survey sources for which only photometric redshifts are available. One important source of systematic uncertainty is the mismatch in photometric properties between galaxies in the Euclid survey and the reference objects. We develop a method to degrade the photometry of objects with deep photometry to match the properties of any shallower survey in the multi-band photometric space, preserving all the correlations between the fluxes and their uncertainties. We compare our transfer method with more demanding image-based methods, such as Balrog from the Dark Energy Survey Collaboration. According to metrics, our method outperforms Balrog. We implement it in the redshift distribution reconstruction, based on the self-organising map approach of arXiv:1509.03318, and test it using a realistic sample from the Euclid Flagship Simulation. We find that the key ingredient is to ensure that the reference objects are distributed in the colour space the same way as the wide-survey objects, which can be efficiently achieved with our transfer method. In our best implementation, the mean redshift biases are consistently reduced across the tomographic bins, bringing a significant fraction of them within the Euclid accuracy requirements in all tomographic bins. Equally importantly, the tests allow us to pinpoint which step in the calibration pipeline has the strongest impact on achieving the required accuracy. Our approach also reproduces the overall redshift distributions, which are crucial for applications such as angular clustering.

astro-ph.CO↗

Euclid Quick Data Release (Q1): VIS processing and data products

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 (PV) and Q1 data. 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 $0.\!^{\prime\prime}16$. The stacked images (combining four nominal and two short exposures) reach $I_\mathrm{E} = 25.6$ ($10σ$, measured as the variance of $1.\!^{\prime\prime}3$ 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.

astro-ph.IM↗

Euclid preparation. Review of forecast constraints on dark energy and modified gravity

The Euclid mission has been designed to provide, as one of its main deliverables, information on the nature of the gravitational interaction, which determines the expansion of the Universe and the formation of structures. Thus, Euclid has the potential to test deviations from general relativity that will allow us to shed light on long-lasting problems in the standard cosmological model, $Λ$CDM. Euclid will mainly do this by using two complementary probes: weak gravitational lensing and galaxy clustering. In this paper we review pre-launch Euclid analyses for dark energy and modified gravity. These include forecast constraints with future Euclid data on cosmological parameters for different cosmological models, such as a time-varying dark energy component, phenomenological modifications of the perturbation sector and specific modified gravity models, with further extensions that include neutrino physics and the coupling to the electromagnetic sector through the fine-structure constant. We review the study of the impact of nonlinear clustering methods on beyond-$Λ$CDM constraints with Euclid. This is of fundamental importance to efficiently predict the large-scale clustering of matter and dark matter halos, given that we will have access to a wealth of information on scales beyond the linear regime. We inspect the extension of theoretical predictions for observable quantities in alternative cosmologies to $Λ$CDM at fully nonlinear scales by means of $N$-body simulations. We discuss the impact of relativistic corrections in extended cosmological models. Overall, this review highlights the significant potential of the Euclid mission to tightly constrain parameters of dark energy and modified gravity models, or perhaps to detect possible signatures of a $Λ$CDM failure.

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

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

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

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

astro-ph.IM↗

Euclid: The first statistical census of dusty and massive objects in the ERO/Perseus field

Our comprehension of the history of star formation at $z>3$ relies on rest-frame UV observations, yet this selection misses the most dusty and massive sources, yielding an incomplete census at early times. Infrared facilities such as Spitzer and the James Webb Space Telescope have revealed a hidden population at $z=3$-$6$ with extreme red colours, named HIEROs (HST-to-IRAC extremely red objects), identified by the criterion $H_{\mathrm{E}}-\mathrm{ch2}>2.25$. Recently, Euclid Early Release Observations (ERO) have made it possible to further study such objects by comparing Euclid data with ancillary Spitzer/IRAC imaging. We investigate a $232$ arcmin$^2$ area in the Perseus field using VIS and NISP photometry, complemented by the four Spitzer channels and ground-based MegaCam bands ($u$, $g$, $r$, ${\rm H}α$, $i$, $z$). Applying the colour cut yields $121$ HIEROs; after removing globular clusters, brown dwarfs, and unreliable cases through visual inspection of multiband cutouts, we obtain a final sample of $42$ robust HIEROs. Photometric redshifts and physical properties are estimated with the SED-fitting code Bagpipes. From the resulting $z_{\mathrm{phot}}$ and $M_*$ values, we compute the galaxy stellar mass function at $3.5<z<5.5$. Even after excluding possible AGN hosts or systems where the stellar mass may be overestimated, the high-mass end remains comparable to previous determinations, suggesting the true abundance could be higher. These results highlight the importance of further study of this obscured population to assess its role in the cosmic star-formation rate density and its consistency with galaxy-formation models, demonstrating Euclid's capability to advance our understanding of dust-hidden star formation across early epochs.

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Euclid Structural-Thermal-Optical Performance

The Euclid system performance is defined in terms of image quality metrics tuned to the weak gravitational lensing (WL) cosmological probe. WL induces stringent requirements on the shape and stability of the VIS instrument system point spread function (PSF). The PSF is affected by error contributions from the telescope, the focal plane and image motion, and is controlled by a global error budget with error allocations to each contributor. Aims. During spacecraft development, we verified through a structural-thermal-optical performance (STOP) analysis that the built and verified telescope with its spacecraft interface meets the in-orbit steady-state and transient image quality requirements. Methods. For the purposes of the STOP analysis, a detailed finite-element mathematical model was set up and a standard set of test cases, both steady-state and transient, was defined, comprising combinations of worst-case boundary conditions. Results. The STOP analysis addressed the interaction of all spacecraft components in transmitting temperature-induced loads that lead to optical train deformation. The results of the prelaunch analysis demonstrated that temperature-induced optical perturbations will be well below the allowable limits for all permitted observing conditions. During the first year in orbit, we used the STOP analysis predictions to help interpret the measured performance as a function of environmental variables. Unpredicted disturbances were discovered and unexpected sensitivities were revealed. In-orbit temperature variations are small (<300 mK) and so are their effects on the telescope structure, but they are detected in the time histories of the image quality metrics and are a non-negligible factor in the PSF stability budget demanded by the WL science. Taking everything into account, our analysis confirms the excellent overall performance of the telescope.

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Euclid preparation: LXXXI. The impact of nonparametric star formation histories on spatially resolved galaxy property estimation using synthetic Euclid images

We analyzed the spatially resolved and global star formation histories (SFHs) for a sample of 25 TNG50-SKIRT Atlas galaxies to assess the feasibility of reconstructing accurate SFHs from Euclid-like data. This study provides a proof of concept for extracting the spatially resolved SFHs of local galaxies with Euclid, highlighting the strengths and limitations of SFH modeling in the context of next-generation galaxy surveys. We used the spectral energy distribution (SED) fitting code Prospector to model both spatially resolved and global SFHs using parametric and nonparametric configurations. The input consisted of mock ultraviolet--near-infrared photometry derived from the TNG50 cosmological simulation and processed with the radiative transfer code SKIRT. We show that nonparametric SFHs provide a more effective approach to mitigating the outshining effect by recent star formation, offering improved accuracy in the determination of galaxy stellar properties. Also, we find that the nonparametric SFH model at resolved scales closely recovers the stellar mass formation times (within 0.1~dex) and the ground truth values from TNG50, with an absolute average bias of $0.03$~dex in stellar mass and $0.01$~dex in both specific star formation rate and mass-weighted age. In contrast, larger offsets are estimated for all stellar properties and formation times when using a simple $τ$-model SFH, at both resolved and global scales, highlighting its limitations. These results emphasize the critical role of nonparametric SFHs in both global and spatially resolved analyses, as they better capture the complex evolutionary pathways of galaxies and avoid the biases inherent in simple parametric models.

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EMU and Euclid: Detection of a radio-optical galaxy clustering cross-correlation signal between the Evolutionary Map of the Universe and Euclid

Synergies between large-scale radio-continuum and optical/near-infrared galaxy surveys are a powerful tool for cosmology. Cross-correlating these surveys can constrain the redshift distribution of radio sources, mitigate systematic effects, and place constraints on cosmological models. We perform the first measurement of the clustering cross-spectrum between radio-continuum sources in the Evolutionary Map of the Universe (EMU) survey and galaxies from the ESA Euclid satellite mission's Q1 release. Our goal is to detect and characterise the cross-correlation signal, test its robustness against systematic effects, and compare our measurements with theoretical predictions. We use data from the Australian SKA Pathfinder's EMU Main Survey, which overlaps with the Euclid Deep Field South. We generate two radio-source catalogues using different source finders to create galaxy maps. We measure the harmonic-space cross-correlation signal using a pseudo-spectrum estimator. The measured signal is compared to theoretical predictions based on a ΛCDM cosmology, using several models for the EMU source redshift distribution and bias. We report detection above 8σ of the cross-correlation signal consistent across all tested models and data sets. The measured cross-spectra from the two radio catalogues are in excellent agreement, demonstrating that the cross-correlation is robust against the choice of source-finding algorithm. The measured signal also agrees with theoretical models developed from previous cross-correlation studies and simulations. This pathfinder study establishes a statistically significant cross-correlation between EMU and Euclid. The robustness of the signal is a crucial validation of the methodology, paving the way for future large-scale analyses leveraging the full power of this synergy to constrain cosmological parameters and our understanding of galaxy evolution.

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Euclid Quick Data Release (Q1): Hunting for luminous z > 6 galaxies in the Euclid Deep Fields -- forecasts and first bright detections

The evolution of the rest-frame ultraviolet luminosity function (UV LF) is a powerful probe of early star formation and stellar mass build-up. At z > 6, its bright end (MUV < -21) remains poorly constrained due to the small volumes of existing near-infrared (NIR) space-based surveys. The Euclid Deep Fields (EDFs) will cover 53 deg^2 with NIR imaging down to 26.5 AB, increasing area by a factor of 100 over previous space-based surveys. They thus offer an unprecedented opportunity to select bright z > 6 Lyman break galaxies (LBGs) and constrain the UV LF's bright end. With NIR coverage extending to 2um, Euclid can detect galaxies out to z = 13. We present forecasts for the number densities of z > 6 galaxies expected in the final EDF dataset. Using synthetic photometry from spectral energy distribution (SED) templates of z = 5--15 galaxies, z = 1--4 interlopers, and Milky Way MLT dwarfs, we explore optimal selection methods for high-z LBGs. A combination of S/N cuts with SED fitting (from optical to MIR) yields the highest-fidelity sample, recovering >76% of input z > 6 LBGs while keeping low-z contamination <10%. This excludes instrumental artefacts, which will affect early Euclid releases. Auxiliary data are critical: optical imaging from the Hyper Suprime-Cam and Vera C. Rubin Observatory distinguishes genuine Lyman breaks, while Spitzer/IRAC data help recover z > 10 sources. Based on empirical double power-law LF models, we expect >100,000 LBGs at z = 6-12 and >100 at z > 12 in the final Euclid release. In contrast, steeper Schechter models predict no z > 12 detections. We also present two ultra-luminous (MUV < -23.5) candidates from the EDF-N Q1 dataset. If their redshifts are confirmed, their magnitudes support a DPL LF model at z > 9, highlighting Euclid's power to constrain the UV LF's bright end and identify the most luminous early galaxies for follow-up.

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Euclid preparation LXXIX. Using mock low surface brightness dwarf galaxies to probe Euclid Wide Survey detection capabilities

Local Universe dwarf galaxies can serve as both cosmological and mass assembly probes. Deep surveys have enabled the study of these objects down to the low surface brightness (LSB) regime. In this paper, we estimate Euclid's dwarf detection capabilities as well as limits of its MERge processing function (MER pipeline), which is responsible for producing the stacked mosaics and final catalogues. To do this, we injected mock dwarf galaxies in a real Euclid Wide Survey (EWS) field in the VIS band and compared the input catalogue to the final MER catalogue. The mock dwarf galaxies were generated using simple Sersic models with structural parameters (including size and surface brightness) drawn from observed dwarf galaxy catalogues. These simulations represent an idealised case in the sense they do not account for additional factors such as ellipticity, morphology, or crowding. To characterise the detected dwarfs, we used the mean surface brightness inside the effective radius SB_e (in mag arcsec^-2). The final MER catalogues achieve completenesses of 91% for SB_e in [21,24] and 54% for SB_e in [24,28]. These numbers do not take into account possible contaminants, including confusion with background galaxies at the location of the dwarfs. After taking those effects into account, they respectively became 86% and 38%. The MER pipeline performs a final local background subtraction with a small mesh size, leading to a flux loss for galaxies with R_e > 10 arcsec. By using the final MER mosaics and reinjecting this local background, we obtained an image in which we recover reliable photometric properties for objects under the arcminute scale. This background-reinjected product is thus suitable for the study of Local Universe dwarf galaxies. Euclid's data reduction pipeline serves as a test bed for other deep surveys, particularly regarding background subtraction methods, a key issue in LSB science.

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\textit{Euclid}: From Galaxies to Gravitational Waves -- Forecasting Stochastic Gravitational Wave Background Anisotropies and Their Cross-Correlation

We estimate the amplitude and spatial anisotropy in the stochastic gravitational wave background (SGWB) energy density due to compact binary coalescence (CBC) events: binary black holes (BBH), binary neutron stars (BNS), and black hole-neutron star (BHNS) mergers. Our starting point is the Flagship Simulation Galaxy Catalogue developed by the Euclid Consortium. For each galaxy in the Catalogue, we use the simulated mass and starformation to constrain the galaxy's star-formation history, and predict its contribution to the gravitational-wave energy density through CBC mergers. Combining such contributions from all galaxies in the Catalogue results in a prediction for the frequency spectrum and spatial anisotropy of the CBC SGWB. We also compare this prediction to semi-analytical models of SGWB generated by compact binaries. We identify a set of effective parameters that capture the key features of these models, and we apply a Bayesian framework to infer these parameters assuming an ideal scenario of cosmic variance-limited search. This represents the first step toward developing a comprehensive framework that will eventually enable the correlation of SGWB anisotropy and \textit{Euclid} galaxy data, potentially allowing us to extract valuable astrophysical information from this new observable.

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Euclid Quick Data Release (Q1): Identification of massive galaxy candidates at the end of the Epoch of Reionisation

Probing the presence and properties of massive galaxies at high redshift is one of the most critical tests for galaxy formation models. In this work, we search for galaxies with stellar masses M* > 10^10.25 Msun at z in [5,7], i.e., towards the end of the Epoch of Reionisation, over a total of ~23 deg^2 in two of the Euclid Quick Data Release (Q1) fields: the Euclid Deep Field North and Fornax (EDF-N and EDF-F). In addition to the Euclid photometry, we incorporate Spitzer Infrared Camera (IRAC) and ground-based optical data to perform spectral energy distribution (SED) fitting, obtaining photometric redshifts and derived physical parameters. After applying rigorous selection criteria, we identify a conservative sample of 145 candidate massive galaxies with M* > 10^10.25 Msun at z in [5,7], including 5 objects with M* > 10^11 Msun. This makes for a surface density of about 6.3 deg^-2 at z in [5,7], which should be considered a lower limit because of the current depth of the Euclid data (H_E < 24, 5 sigma in Q1). We find that the inferred stellar masses are consistent with galaxy formation models with standard star-formation efficiencies. These massive galaxies have colour excess E(B-V) values up to 0.75, indicating significant dust attenuation in some of them. In addition, half of the massive galaxies have best-fit ages comparable to the age of the Universe at those redshifts, which suggests that their progenitors were formed very early in cosmic time. About 78% of the massive galaxies lie on the star-forming main sequence (MS) in the SFR-M* plane, ~12% are found in the starburst region, and 10% in the transition zone between the MS and starbursts. We find no significant evidence for outshining or AGN contamination that could account for the elevated specific star-formation rates (sSFR) observed in the ~12% of galaxies classified as starbursts.

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