arXiv subjects

L. Guzzo

Publications and source records attributed to L. Guzzo.

At least 19 recordsLinked to original sources

arXiv2026

Euclid. A two-point correlation approach to diagnosing star-related systematics in the Euclid spectroscopic survey

The Euclid spectroscopic survey will measure galaxy clustering with unprecedented precision, requiring stringent control of observational and instrumental systematics. Star-related effects may contaminate spectroscopic images through photometric persistence and imperfect masking of stars. We characterized their impact on galaxy clustering analyses, focusing on angular features identifiable in the data. We used angular and spatial auto- and cross-correlation statistics. For galaxies, we used mock spectroscopic catalogues from the EuclidLargeMocks in a 330 deg2 region of the Euclid Wide Survey (EWS). For stars, we used Gaia and 2MASS catalogues in the same area. To simulate photometric persistence, we implemented a simplified detector-level model calibrated on spectroscopic measurements and varied its strength to introduce different interloper fractions. For stellar masking, we modelled inconsistencies between the mask applied to the data and to the random catalogue. We measured star-star, galaxy-galaxy, and star-galaxy angular correlation functions using the Landy--Szalay estimator, and quantified deviations from the expected null star-galaxy correlation. We also evaluated the large-scale impact of such systematics through the three-dimensional two-point correlation function (2PCF). Photometric persistence produces a characteristic feature in the star-galaxy angular cross-correlation at scales of order 100", corresponding to the Euclid dithering pattern and grism dispersion geometry, and a spurious positive signal approximately constant up to 1{\deg}. Star-galaxy cross-correlation can detect residual persistence at contamination levels as low as 10% in a Data Release 1 spectroscopic catalogue. In contrast, stellar-mask mismatches produce strong small-scale angular signatures but have negligible impact on the large-scale 2PCF under realistic EWS conditions.

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arXiv2026

Euclid: A UV-faint quasar in a highly luminous star-forming host galaxy at $z \approx 7.7$

Constraining the co-evolution of supermassive black holes and their host galaxies in the first billion years after the Big Bang is essential for understanding the formation of the earliest cosmic structures. Here, we present IRAM/NOrthern Extended Millimeter Array (NOEMA) observations of the $z \approx 7.7$ quasar EUCL\,J125308.55+705432.3, recently discovered in the first data release of the Euclid Wide Survey. We report the most distant detections of [CII] 158$\mu\mathrm{m}$ and cold dust emission in a quasar host to date. The [CII] emission line sets the systemic redshift at $z=7.6980\pm0.0004$. The source exhibits luminosities of $L_{\rm FIR}=3.6\times10^{12}\,L_{\odot}$ and $L_{[CII]}=2\times10^9\,L_{\odot}$, respectively, a dust mass of 1.4$\times 10^{8}\,M_{\odot}$, and a dynamical mass in the range 0.33-1.3$\times10^{10}\,M_{\odot}$. Remarkably, despite being nearly two magnitudes fainter in the rest-frame UV ($M_{1450}=-24.06$) than previously known $z\approx7.5$ quasars ( $\sim-$26.5), EUCL\,J125308.55+705432.3 exhibits the brightest [CII] emission among them. This indicates that the host galaxy is actively star-forming, with a star-formation rate $>250\,M_{\odot}\,\mathrm{yr}^{-1}$, consistent with recent findings that UV-faint quasars at $z>6$ preferentially reside in [CII]-luminous galaxies. The UV-faintness likely reflects dust obscuration or sub-Eddington accretion, rather than lower host mass, suggesting these systems are at a different stage in their evolution compared to UV-bright quasars. These IRAM/NOEMA observations highlight the power of combining Euclid's wide-area quasar discovery potential with submillimetre follow-up observations to characterise the host galaxies of early supermassive black holes across a broader redshift and luminosity range than previously accessible.

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arXiv2026

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

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

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arXiv2026

Euclid preparation. First investigation of the impact of cross-contamination on spectroscopic redshift measurements with pixel-level simulations

We present a study on simulated data focused on understanding the performance of the spectroscopic redshift measurements with the Near-Infrared Spectrometer and Photometer (NISP) instrument on Euclid. Simulations include scenarios with different levels of cross-contamination arising from overlapping spectra of nearby sources, which represents one of the main drawbacks of slitless spectroscopy. We present a new analysis based on pixel-level simulations of the NISP images, with the data processed using the Euclid spectroscopic pipeline. We first consider an idealised case with non-overlapping spectra to assess the accuracy and reliability of the redshift measurement as a function of the flux of the H-alpha emission line and galaxy size. We then introduce more realistic contamination scenarios, distinguishing between two contributions: contamination from H-alpha emitters, which are the Euclid targets for cosmological analyses, and contamination from all other galaxies. In the second case, we analyse the impact of cross-contamination with an increasing number of contaminants, from the brighter to the fainter galaxies. Given that our results show no clear evidence that sources fainter than magnitude 20 degrade redshift measurements, we conservatively restrict our analysis to galaxies with magnitudes up to 24. In particular, we provide a preliminary estimate that contamination from galaxies within the same redshift range as the target sample contributes to about 4% of the total degradation due to cross-contamination from all galaxies.

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arXiv2026

\textit{Euclid} preparation. Baryon acoustic oscillations extraction techniques: comparison and optimisation

We present the first end-to-end validation of the Euclid baryon acoustic oscillation (BAO) analysis pipeline, encompassing density-field reconstruction, two-point correlation function measurement, and cosmological-parameter inference. Using eight Euclid-like mock catalogues from each of four Flagship I snapshots, designed to reproduce the expected statistical properties of the first Euclid data release (DR1), we assess the two standard BAO reconstruction methods based on the Zel'dovich approximation, RecSym and RecIso, across $0.9 \leq z \leq 1.8$. The pipeline introduces several methodological advances: an emulator-based model evaluator (Bora.jl) combined with a Hamiltonian Monte Carlo sampler (NUTS), achieving more than a 500-fold speed-up relative to standard Markov chain Monte Carlo, and a semi-analytical covariance estimator (BeXiCov+WinCov) that enables robust error estimates from only eight mock realisations while remaining stable under fiducial-cosmology variations. These components ensure computational efficiency while reducing the risk of underestimating parameter uncertainties. Both reconstruction schemes yield unbiased BAO measurements across all redshifts and analysis choices, including smoothing scale and fiducial cosmology. In each snapshot, reconstruction enhances the figure of merit for $\{\Omega_m, H_0 r_s\}$ by $\sim3$, equivalent to tripling the effective survey volume. Combining the four redshift bins, the improvement remains substantial, with BAO-only constraints reaching $\sim10\%$ precision on $\Omega_m$ and $\sim3\%$ on $H_0 r_s$. Results from RecSym and RecIso are consistent within uncertainties, though we recommend RecSym during testing due to its lower sensitivity to covariance variations. These findings establish the accuracy, robustness, and scalability of the Euclid BAO pipeline for DR1, providing a solid foundation for future cosmological analyses.

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arXiv2026

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

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

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arXiv2026

Euclid Quick Data Release (Q1). AstroVink: A vision transformer approach to find strong gravitational lens systems

We present AstroVink, a vision transformer classifier designed for automated identification of strong lens candidates in Euclid imaging. We build upon the DINOv2 encoder, fine tuned to distinguish between lens and non-lens galaxies. Our base model, trained on simulated strong lens systems and labelled non lenses, recovers 88 of the 110 lens candidates within the top 500 ranked candidates, corresponding to an inspection efficiency of one lens per 5.7 inspected objects in our test set. After the Q1 data release, which yielded about 500 lens candidates, we retrained the model using high confidence lens candidates and new negatives, initially flagged as potential lenses by other classifiers but rejected during visual inspection. The retrained network further improves performance, achieving recovery of all 110 systems within the same ranking and reducing the inspection effort to one lens per 4.5 inspected objects, demonstrating that incorporating real examples significantly enhances model generalisation. An analysis of training subsets revealed that the inclusion of realistic negative examples played a key role in this improvement. Finally, we applied the retrained model to the Q1 original selection of 1.08M targets, followed by a new round of Space Warps citizen science inspection and expert vetting, where we identified a total of eight Grade A and 26 Grade B new lens candidates. These results demonstrate that transformer based architectures can recover strong lens candidates with high efficiency in real Euclid data, while substantially reducing the number of candidates requiring visual inspection.

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arXiv2026

Euclid. Populating a dark universe with galaxies using SciPIC

High-fidelity galaxy mocks are crucial for validating analysis pipelines and for cosmological inference. In this context, the Science Pipeline at PIC (SciPIC) is a pipeline specifically designed for the fast generation of synthetic galaxy catalogues from the halo properties identified in cosmological simulations. SciPIC delivers galaxy catalogues that aim to reproduce the observed luminosity function and clustering above a given flux detection limit over a wide redshift range. In this work, we introduce SciPICal, an automated pipeline that calibrates the parameters that set the main mock galaxy properties, namely number density, luminosities, colours, and positions. The pipeline is applied to the Euclid Flagship 2 Wide and Deep halo catalogues, specifically built to support the \textit{Euclid} wide and deep surveys. Compared to the recently released Flagship 2 Wide mock, our calibrated version improves the clustering predictions by approximately 50\% based on chi-squared values. Furthermore, we produce the Euclid Deep mock catalogue, which reaches up to $z = 10$ by populating a light-cone and a complementary snapshot at $z = 0$. We validate these catalogues using measurements from spectroscopic and photometric galaxy surveys, as well as with results from a hydrodynamical simulation. The obtained good agreement (within $15\%$ for most of the samples) in the clustering predictions across the different galaxy samples considered, validates our calibration strategy and demonstrates the strong predictive power of the generated mocks. This pipeline will allow us to improve the methodology applied in assigning the galaxy properties and ensures that the galaxy mocks remain up-to-date by incorporating constraints from upcoming observational data in the calibration procedure.

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arXiv2026

Euclid preparation. Galaxy power spectrum modelling in redshift space

Accurate modelling of redshift-space distortions (RSD) is essential for maximizing the cosmological information extracted from large galaxy redshift surveys. In preparation for the forthcoming analysis of the Euclid spectroscopic data, we investigate three approaches to modelling RSD effects on the power spectrum multipoles of mock H$\alpha$ emission line galaxies. We focus on two one-loop perturbation theory models -- the effective field theory (EFT) and velocity difference generator (${\rm VDG_ \infty}$) -- which differ in their treatment of the real-to-redshift space mapping on small scales, and a third approach, the BACCO emulator, which adopts a hybrid strategy combining perturbation theory with high-resolution N-body simulations. We assess the ability of these models to recover key cosmological parameters, including the expansion rate $h$, the cold dark matter density parameter $\omega_{\rm c}$, and the scalar amplitude $A_{\rm s}$, across four redshift bins spanning $0.9 \leq z \leq 1.8$. In each bin, we find that ${\rm VDG_ \infty}$ and BACCO outperform the EFT model across all scales up to $k_{max} \lesssim 0.35 h\,Mpc^{-1} $. While BACCO saturates in constraining power at intermediate scales and higher redshift, the ${\rm VDG_ \infty}$ model continues to improve parameter constraints beyond $k_{max} \gtrsim 0.30 h\,Mpc^{-1}$. The EFT model, although robust on large scales, exhibits significant parameter biases for $k_{max} \gtrsim 0.25 h\,Mpc^{-1}$, limiting its applicability to Euclid-like H$\alpha$ samples. Among the full perturbation theory-based models, the enhanced treatment of small-scale RSD effects in ${\rm VDG_ \infty}$ improves cosmological parameter constraints by up to a factor of two.

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arXiv2026

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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arXiv2025

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 {\Lambda}CDM cosmology, using several models for the EMU source redshift distribution and bias. We report detection above 8{\sigma} 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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arXiv2025

Euclid preparation. XCII. Controlling angular systematics in the Euclid spectroscopic galaxy sample

We present the strategy used to identify and mitigate potential sources of angular systematics in the \textit{Euclid} spectroscopic galaxy survey, and we quantify their impact on galaxy clustering measurements and cosmological parameter estimation. We first surveyed the \textit{Euclid} processing pipeline to identify all evident, potential sources of systematics, and classified them into two broad classes: angular systematics, which modulate the galaxy number density across the sky, and catastrophic redshift errors, which lead to interlopers in the galaxy sample. We then used simulated spectroscopic surveys to test our ability to mitigate angular systematics by constructing a random catalogue that represents the `visibility mask' of the survey; this is a dense set of intrinsically unclustered objects, subject to the same selection effects as the data catalogue. The construction of this random catalogue relies on a detection model, which gives the probability of reliably measuring the galaxy redshift as a function of the signal-to-noise ratio (S/N) of its emission lines. We demonstrate that, in the ideal case of a perfect knowledge of the visibility mask, the galaxy power spectrum in the presence of systematics is recovered, to within sub-per cent accuracy, by convolving a theory power spectrum with a window function obtained from the random catalogue itself. In the case of only approximate knowledge of the visibility mask, we test the stability of power spectrum measurements and cosmological parameter posteriors by using perturbed versions of the random catalogue. We find that significant effects are limited to very large scales, and parameter estimation remains robust; the most impacting effects are connected to the calibration of the detection model.

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arXiv2025

Euclid preparation: LXXXVII. Non-Gaussianity of 2-point statistics likelihood: Precise analysis of the matter power spectrum distribution

We investigate the non-Gaussian features in the distribution of the matter power spectrum multipoles. Using the COVMOS method, we generate 100\,000 mock realisations of dark matter density fields in both real and redshift space across multiple redshifts and cosmological models. We derive an analytical framework linking the non-Gaussianity of the power spectrum distribution to higher-order statistics of the density field, including the trispectrum and pentaspectrum. We explore the effect of redshift-space distortions, the geometry of the survey, the Fourier binning, the integral constraint, and the shot noise on the skewness of the distribution of the power spectrum measurements. Our results demonstrate that the likelihood of the estimated matter power spectrum deviates significantly from a Gaussian assumption on nonlinear scales, particularly at low redshift. This departure is primarily driven by the pentaspectrum contribution, which dominates over the trispectrum at intermediate scales. We also examine the impact of the finiteness of the survey geometry in the context of the Euclid mission and find that both the shape of the survey and the integral constraint amplify the skewness.

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arXiv2025

Euclid Quick Data Release (Q1). Searching for giant gravitational arcs in galaxy clusters with mask region-based convolutional neural networks

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust, automated methods capable of handling the immense data volume generated. In this work, we present an advanced deep learning (DL) framework based on mask region-based convolutional neural networks (Mask R-CNNs), designed to autonomously detect and segment bright, strongly-lensed arcs in Euclid's multi-band imaging of galaxy clusters. The model is trained on a realistic simulated data set of cluster-scale SL events, constructed by injecting mock background sources into Euclidised Hubble Space Telescope images of 10 massive lensing clusters, exploiting their high-precision mass models constructed with extensive spectroscopic data. The network is trained and validated on over 4500 simulated images, and tested on an independent set of 500 simulations, as well as real Euclid Quick Data Release (Q1) observations. The trained network achieves high performance in identifying gravitational arcs in the test set, with a precision and recall of 76% and 58%, respectively, processing 2'x2' images in a fraction of a second. When applied to a sample of visually confirmed Euclid Q1 cluster-scale lenses, our model recovers 66% of gravitational arcs above the area threshold used during training. While the model shows promising results, limitations include the production of some false positives and challenges in detecting smaller, fainter arcs. Our results demonstrate the potential of advanced DL computer vision techniques for efficient and scalable arc detection, enabling the automated analysis of SL systems in current and future wide-field surveys. The code, ARTEMIDE, is open source and will be available at github.com/LBasz/ARTEMIDE.

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arXiv2025

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 $\Omega_{\rm m}$ and on the power spectrum amplitude $\sigma_8$. 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 $\Omega_{\rm m}$ and $\sigma_8$ parameters. RSDs and photo-$z$ uncertainties also influence the number count covariance, with a significant impact, of about 15--20\%, on the parameter constraints.

astro-ph.CO↗

arXiv2025

Euclid preparation. XCVIII. Cosmology Likelihood for Observables in Euclid (CLOE). 5: Extensions beyond the standard modelling of theoretical probes and systematic effects

Euclid is expected to establish new state-of-the-art constraints on extensions beyond the standard LCDM cosmological model by measuring the positions and shapes of billions of galaxies. Specifically, its goal is to shed light on the nature of dark matter and dark energy. Achieving this requires developing and validating advanced statistical tools and theoretical prediction software capable of testing extensions of the LCDM model. In this work, we describe how the Euclid likelihood pipeline, Cosmology Likelihood for Observables in Euclid (CLOE), has been extended to accommodate alternative cosmological models and to refine the theoretical modelling of Euclid primary probes. In particular, we detail modifications made to CLOE to incorporate the magnification bias term into the spectroscopic two-point correlation function of galaxy clustering. Additionally, we explain the adaptations made to CLOE's implementation of Euclid primary photometric probes to account for massive neutrinos and modified gravity extensions. Finally, we present the validation of these CLOE modifications through dedicated forecasts on synthetic Euclid-like data by sampling the full posterior distribution and comparing with the results of previous literature. In conclusion, we have identified in this work several functionalities with regards to beyond-LCDM modelling that could be further improved within CLOE, and outline potential research directions to enhance pipeline efficiency and flexibility through novel inference and machine learning techniques.

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arXiv2025

Euclid: Discovery of bright $z\simeq7$ Lyman-break galaxies in UltraVISTA and Euclid COSMOS

We present a search for $z\simeq7$ Lyman-break galaxies using the $1.72 \, \rm{deg}^2$ near-infrared UltraVISTA survey in the COSMOS field, reaching $5\,\sigma$ depths in $Y$ of 26.2. We incorporate deep optical and Spitzer imaging for a full spectral energy distribution (SED) fitting analysis. We find 289 candidate galaxies at $6.5\leq z \leq 7.5$ covering $-22.6 \leq M_{\rm UV} \leq -20.2$, faint enough to overlap with Hubble Space Telescope studies. We conduct a separate selection by including complementary Euclid performance verification imaging (reaching $5\,\sigma$ depths of $26.3$), yielding 140 galaxies in $0.65 \, \rm{deg}^2$, with 38 sources unique to this sample. We compute the rest-frame UV luminosity function (UV LF) from our samples, extending below the knee ($M^*=-21.14^{+0.28}_{-0.25}$). We find that the shape of the UV LF is consistent with both a Schechter function and double-power law (DPL) at the magnitudes probed by this sample, with a DPL preferred at $M_{\rm UV}<-22.5$ when bright-end results are included. The UltraVISTA+Euclid sample provides a clean measurement of the LF due to the overlapping near-infrared filters identifying molecular absorption features in the SEDs of ultra-cool dwarf interlopers, and additional faint galaxies are recovered. A comparison with JWST LFs at $z>7$ suggests a gentle evolution in the bright-end slope, although this is limited by a lack of robust bright-end measurements at $z>9$. We forecast that in the Euclid Deep Fields, the removal of contaminant ultra-cool dwarfs as point sources will be possible at $J_{\rm E} < 24.5$. Finally, we present a high-equivalent-width Lyman-$\alpha$ emitter candidate identified by combining HSC, VISTA, and Euclid broadband photometry, highlighting the synergistic power these instruments will have in the Euclid Auxiliary Fields for identifying extreme sources in the Epoch of Reionisation.

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arXiv2025

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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