arXiv subjects

S. Camera

Publications and source records attributed to S. Camera.

At least 73 records · Page 4Linked to original sources

arXiv2026

Euclid preparation. Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing

One of the $\textit{Euclid}$ mission's key projects is the so-called 3$\times$2pt analysis, that is, the combination of cosmic shear, photometric galaxy clustering, and galaxy-galaxy lensing. Although $\textit{Euclid}$ has established quality requirements for the photo-$z$ accuracy needed for the weak lensing galaxy sample, no such requirements have been set for the photometric clustering sample. In this paper, we investigate the impact of redshift uncertainties on $\textit{Euclid}$'s photometric galaxy clustering analysis and its combination with weak gravitational lensing, focusing on data release 1 (DR1). In particular, we study whether having precise knowledge of the mean of the redshift distributions per bin is sufficient to avoid biases in the resulting cosmological constraints or whether accuracy in the higher-order moments of the distribution is required. We evaluate the results based on their constraining power on $w_{\mathrm{0}}$ and $w_{a}$ and define thresholds for the precision and accuracy of $\textit{Euclid}$'s redshift distribution of the photometric clustering sample. We find that the redshift distributions of the photometric clustering sample must be known at an accuracy of 0.004(1+$z$) in the mean in order to recover 80$\%$ of the constraining power in $\textit{Euclid}$'s DR1 $w_{\mathrm{0}}w_{a}$CDM 3$\times$2pt analysis. The impact of the uncertainty on the width is negligible, provided the mean redshift is constrained with sufficient accuracy. For most sources of redshift distribution error, attaining the requirement on the mean will also reduce uncertainty in the width well below the required level.

astro-ph.CO↗

arXiv2026

Euclid Quick Data Release (Q1). The first Euclid view of Planck galaxy protocluster candidates at cosmic noon

[ABRIGED ABSTRACT] A large catalogue of candidate galaxy protoclusters with high star-formation rates was produced by the Planck collaboration. We search, in the first data release (Q1) of the Euclid survey, for the visible and infrared counterparts of the Planck galaxy protocluster candidates expected to be above $z > 1.5$. Eight of them are in Euclid Q1. Our goal is to investigate the optical nature of these overdensities previously detected in the submillimetre wavelength range. We search for overdensities using the DETECTIFz algorithm, an overdensity finder based on Delaunay tessellation that uses photometric redshift probability distributions through Monte Carlo simulations. Focusing our search on the eight high-star forming Planck protocluster candidates, we find that two of them have one Euclid counterpart, and six have between two and four Euclid counterparts, which amounts to a total of 20 Euclid counterparts. These Euclid counterparts lie at photometric redshifts $1.4<z_{\rm ph} < 2.7$ and 12 of them also have partial Herschel coverage. All detections have also been confirmed by at least one other independent protocluster detection algorithm. We study the colours, derived stellar masses and star-formation rates (SFRs) of the detected member galaxies of those protocluster candidate counterparts. We also estimate the total stellar masses, SFRs, and the halo mass lower limits for all Euclid protocluster candidates. We find that in the dark matter halo mass ($M_{\rm h}$) / redshift plane, these Planck and Euclid overdense regions lie in the region $12.6 <\log_{10} (M_{\rm h}/M_\odot)< 13.4$, $1.4<z< 2.7$. This means that the halos of our objects are expected to have experienced a transition between cold flows in hot media to accretion of hot material.

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arXiv2026

Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine F -- Bright and low-redshift strong lenses

We present 72 additional galaxy-galaxy strong lenses that complement the sample discovered in the Euclid Quick Release 1 data (63.1 deg^2) of the Strong Lens Discovery Engine (SLDE) papers A-E. It is shown that previous pre-selection of potential lenses, which excluded objects from the Gaia catalogue, led to missing several bright and low-redshift strong lenses, adding more than 10% new strong lens candidates compared to the previous search. In total, the catalogue includes 38 "grade A" (confident) and 34 "grade B" (probable) candidates. These lenses are identified through a combination of two independent searches for bright nearby objects: one based on machine-learning models followed by expert visual inspection, and the other based solely on expert visual inspection, targeting objects not included in the initial machine-learning selection (a limitation identified only after extensive visual inspection). With these additional strong lens candidates, we augment the expected number of high-confidence candidates in the Euclid Wide Survey from previous forecasts to 120000. Detailed semi-automated lens modelling confirms at least 41 systems out of 72, a fraction consistent with that found in SLDE A (315 out of 488). These include: multiple edge-on disc lenses; sources with arcs near the lens centre; "red sources"; and an edge-on disk galaxy lensing a galaxy merger, producing two sets of lensed features, an Einstein ring and a doubly imaged component. The median redshift of these systems is $Δ$ z ~ 0.3 lower than that of the SLDE A sample.

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arXiv2026

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.

astro-ph.CO↗

arXiv2026

Euclid preparation. The impact of redshift interlopers on the two-point correlation function analysis

The Euclid survey aims to measure the spectroscopic redshift of emission-line galaxies by identifying the H$\,α$ line in their slitless spectra. This method is sensitive to the signal-to-noise ratio of the line, as noise fluctuations or other strong emission lines can be misidentified as H$\,α$, depending on redshift. These effects lead to catastrophic redshift errors and the inclusion of interlopers in the sample. We forecast the impact of such redshift errors on galaxy clustering measurements. In particular, we study the effect of interloper contamination on the two-point correlation function (2PCF), the growth rate of structures, and the Alcock-Paczynski (AP) parameters. We analyze 1000 synthetic spectroscopic catalogues, the EuclidLargeMocks, designed to match the area and selection function of the Data Release 1 (DR1) sample. We estimate the 2PCF of the contaminated catalogues, isolating contributions from correctly identified galaxies and from interlopers. We explore different models with increasing complexity to describe the measured 2PCF at fixed cosmology. Finally, we perform a cosmological inference and evaluate the systematic error on the inferred $fσ_8$, $α_{\parallel}$ and $α_{\perp}$ values associated with different models. Our results demonstrate that a minimal modelling approach, which only accounts for an attenuation of the clustering signal regardless of the type of contaminants, is sufficient to recover the correct values of $fσ_8$, $α_{\parallel}$, and $α_{\perp}$ at DR1. The accuracy and precision of the estimated AP parameters are largely insensitive to the presence of interlopers. The adoption of a minimal model induces a 1%-3% systematic error on the growth rate of structure estimation, depending on the redshift. However, this error remains smaller than the statistical error expected for the Euclid DR1 analysis.

astro-ph.CO↗

arXiv2026

Euclid preparation. Cosmology Likelihood for Observables in Euclid (CLOE). 2. Code implementation

We provide a description of the code implementation and structure of Cosmology Likelihood for Observables in Euclid (CLOE), developed by members of the Euclid Consortium. CLOE is a modular Python code for computing the theoretical predictions of cosmological observables and evaluating them against state-of-the-art data from galaxy surveys such as Euclid in a unified likelihood. This primarily includes the core observables of weak gravitational lensing, photometric galaxy clustering, galaxy-galaxy lensing, and spectroscopic galaxy clustering, but also extended probes such as the clusters of galaxies and cross-correlations of galaxy positions and shapes with the cosmic microwave background. While CLOE has been developed to serve as the unified framework for the parameter inferences in Euclid, it has general capabilities that can serve the broader cosmological community. It is different from other comparable cosmological tools in that it is written entirely in Python, performs the full likelihood calculation, and includes both photometric and spectroscopic observables. We will focus on the primary probes of Euclid and will describe the overall code structure, rigorous code development practices, extensive documentation, unique features, speed optimization, and future development plans. CLOE is publicly available at https://github.com/cloe-org/cloe.

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arXiv2026

Euclid preparation. Simulated galaxy catalogues for non-standard cosmological models

Stage-IV galaxy surveys will provide the opportunity to test cosmological models and the underlying theory of gravity with unparalleled precision. In this context, it is crucial for the Euclid mission to leverage its spectroscopic and photometric probes to systematically investigate and incorporate non-standard cosmological models, including modified gravity, alternative dark energy scenarios, massive neutrinos, and primordial non-Gaussianity. We produce and release publicly simulated galaxy catalogues from a broad suite of non-standard cosmological simulations, which we processed through a model-independent analytical pipeline, making use of Rockstar for halo identification, and a modified version of the SciPic library for the galaxy-halo connection using the halo occupation distribution framework. We investigate their galaxy-clustering characteristics via the multipoles of the 2PCF in redshift space and VDG, a highly performant model for galaxy clustering. Across a wide range of models, the linear growth rate multiplied by the matter density within spheres of radius 12,Mpc, fs12, exhibits a notable robustness to the choice of cosmological template. Compared to previous works, our study extends this result to numerous scenarios with markedly distinct gravitational or dark energy dynamics. We find that the most of the scatter in cosmological parameter inference already appears when using the cosmological model of the simulations as templates. Using a `wrong' template can also introduce an additional scatter, although with smaller amplitude. Often, we find deviations much larger than error bars, meaning that the Gaussian approximation for the covariance might need to be further studied. Future cosmological investigations must broaden their scope to include a diverse array of non-standard theoretical frameworks, extending beyond LCDM and rudimentary dynamic dark energy models.

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arXiv2026

Euclid preparation. Far-infrared predictions for Euclid galaxy catalogues: cluster, protocluster, and field

The MAMBO mock galaxy catalogue, based on the Millennium Simulation with empirically assigned galaxy properties, provides predictions of FIR fluxes and physical parameters of Euclid-detectable galaxies. Predicted FIR flux distributions confirm that only the brightest Euclid sources will be detectable in existing FIR surveys. We employ stacking to measure the mean dust properties as a function of stellar mass and redshift. We find dust temperatures and infrared luminosities increase with redshift across all mass bins, while dust masses remain roughly constant. FIR number counts from MAMBO show overall good agreement with observations, and the total infrared luminosity function reproduces published estimates across most redshift ranges, extending to z~10. Comparing the Euclid Wide and Deep Surveys, we find that the EDS recovers the total IRLF to fainter luminosities and higher redshifts (up to z~6 in $I_E$), although its detectability falls below 80% at z>4, whereas the EWS becomes strongly incomplete beyond z~2. We also examine the dependence of the IRLF on environment. Schechter fits indicate that the faint-end slope $α$ flattens with redshift for cluster and protocluster galaxies, while remaining approximately constant for field populations. Imposing additional detection limits from Herschel-PACS and SPIRE shows that only the most luminous ($L_{IR}$ > $10^{12.5}$ $L_{\odot}$) galaxies remain detectable at z~4, but the limited MAMBO area (3.14$deg^2$) is inadequate for statistically robust (>3$σ$) constraints. Survey areas at least 30 times larger are required. Overall, the MAMBO FIR extension reproduces key number count and IRLF trends, provides realistic predictions for FIR-detected Euclid galaxies, and highlights the importance of synergies with current and future FIR/sub-mm facilities to probe environmental dependence with sufficient depth and area.

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arXiv2026

Euclid: The linear-construction covariance and cosmology

We study the properties of galaxy cluster 2-point correlation function covariance matrices estimated using the linear-construction (LC) method, which is computationally up to 20 times faster than the standard sample-covariance method. Our goal is to assess how well the LC method performs in cosmological parameter estimation compared to the sample covariance. We use a set of 1000 mock dark matter halo catalogues to compute both the LC-covariance and the sample-covariance estimates in four redshift shells. These numerical matrices are used to fit a theoretical four-parameter model for the covariance. We then use the two fitted covariance models in a likelihood function to estimate two cosmological parameters - the matter density parameter $Ω_{\rm m}$ and the amplitude of the matter density fluctuations $σ_8$ - from the simulated mock catalogues. The purpose of this is to validate the LC-covariance-based model against the sample-covariance model. The catalogues were simulated assuming the spatially flat $Λ$CDM cosmology, with $Ω_{\rm m} = 0.30711$ and $σ_8=0.8288$. We find that the parameter posteriors obtained using the sample- and LC-covariance models agree well with each other and with the simulation cosmology. The two pairs of marginalized constraints are $Ω_{\rm m} = 0.307 \pm 0.003$ and $σ_8 = 0.826\pm 0.009$ (sample covariance), and $Ω_{\rm m} = 0.308 \pm 0.003$ and $σ_8 = 0.825 \pm 0.009$ (LC covariance). The posterior widths are the same, and the difference in the median values is less than $0.16\,σ$ for both parameters.

astro-ph.CO↗

arXiv2026

Euclid Quick Data Release (Q1) -- Characteristics and limitations of the spectroscopic measurements

The SPE processing function (PF) of the \Euclid pipeline is dedicated to the automatic analysis of one-dimensional spectra to determine redshifts, line fluxes, and spectral classifications. The first \Euclid Quick Data Release (Q1) delivers these measurements for all $H_\mathrm{E}<22.5$ objects identified in the photometric survey. In this paper, we present an overview of the SPE PF algorithm and assess its performance by comparing its results with high-quality spectroscopic redshifts from the Dark Energy Spectroscopic Instrument (DESI) survey in the Euclid Deep Field North. Our findings highlight remarkable accuracy in successful redshift measurements, with a bias of less than $3 \times 10^{-5}$ in $(z_{\rm SPE}-z_{\rm DESI})/(1+z_{\rm DESI})$ and a high precision of approximately $10^{-3}$. The majority of spectra have only a single spectral feature or none at all. To avoid spurious detections, where noise features are misinterpreted as lines or lines are misidentified, it is therefore essential to apply well-defined criteria on quantities such as the redshift probability or the \ha\ flux and signal-to-noise ratio. Using a well-tuned quality selection, we achieve an 89\% redshift success rate in the target redshift range for cosmology ($0.9<z<1.8$), which is well covered by DESI for $z<1.6$. Outside this range where the \ha\ line is observable, redshift measurements are less reliable, except for sources showing specific spectral features (e.g., two bright lines or strong continuum). Ongoing refinements along the entire chain of PFs are expected to enhance both the redshift measurements and the spectral classification, allowing us to define the large and reliable sample required for cosmological analyses. Overall, the Q1 SPE results are promising, demonstrating encouraging potential for cosmology.

astro-ph.CO↗

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$α$ 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 $ω_{\rm c}$, 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$α$ 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.

astro-ph.CO↗

arXiv2026

Euclid Quick Data Release (Q1): Euclid spectroscopy of quasars. 1. Identification and redshift determination of 3500 bright quasars

The slitless spectroscopy mode of the NISP onboard Euclid has enabled efficient spectroscopy of objects within a large FoV. We present a large and homogeneous sample of bright quasars identified from the Euclid Quick Data Release (Q1) by combining high-purity candidate selections from Gaia and WISE with the NISP spectra. Through visual inspection of the Euclid spectra of these quasar candidates, we identify approximately 3500 quasars with reliable redshifts at $0<z\lesssim 4.8$. Of these, 2686 are new spectroscopic identifications relative to existing public compilations. We generate the first Euclid composite spectrum of quasars covering rest-frame NUV to NIR wavelengths without telluric lines, which will be pivotal to NIR quasar spectral analysis. We obtain an empirical spectroscopic depth of $J_{\rm E}\lesssim 21.5$ and $H_{\rm E}\lesssim 21.3$ at the sensitivity of the Wide Field Survey, beyond which the number of securely identified quasars declines sharply. We analyse VIS morphologies using Sersic and CAS metrics, and a deep-learning PSF fraction to track nuclear dominance. At low redshift ($z<0.5$), obvious host structures are common and a single Sersic model fits about half of the sources; at intermediate redshift ($0.5<z<2$), the nuclear component dominates, with 90% of the Sersic fits saturating at the upper index limit. In this intermediate redshift regime, $f_{\rm PSF}$ is available, and we use it as a more reliable compactness measure than the single-Sersic and CAS parameters to quantify nuclear versus host emission. We also explore the novel Euclid NIR colour space and discuss the role of these quasars in refining AGN selection techniques for future Euclid data releases. The spectroscopic bright quasar catalogue of this work, and the composite quasar spectrum, will be available at https://cdsarc.cds.unistra.fr/. (abridged)

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arXiv2026

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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arXiv2026

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 $5\,σ$ 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 $5\,σ$ 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-$α$ 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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arXiv2026

Euclid: An automated system to match Rubin transient alerts to Euclid observations

The Vera C. Rubin observatory is expected to produce 10 million transient alerts per night in ugrizy filters, whilst Euclid is a visible to near-infrared space telescope engaged in a wide field survey. We present a prototype system to automatically match the transient alerts from Rubin to Euclid observations. The system produces joint light-curves containing both visible and near-infrared photometry, and joint image cutouts. Using Zwicky Transient Facility alerts as a proxy for Rubin, we demonstrate the system in use in cases where Euclid did and did not detect the transient and highlight the value that can be added in each case. For transients detected by Euclid these benefits include identifying the supernovae (SNe) in observations taken prior to ground-based detection, thereby better constraining the explosion time, such as SN 2024pvw detected ~3 d prior to ground based detections. In cases where Euclid did not detect the transient, we demonstrate the benefit of adding Euclid observations to improve host morphology measurements and associations.

astro-ph.IM↗

arXiv2026

The LOFAR Two-metre Sky Survey: VII. Third Data Release

We present the third data release of the LOFAR Two-metre Sky Survey (LoTSS-DR3). The survey images cover 88% of the northern sky and were created from 12,950 hrs of data (18.6 PB) accumulated over 10.5 years. The images were produced through direction-independent and direction-dependent calibration pipelines that correct for instrumental effects as well as spatially and temporally varying ionospheric distortions. In our 120-168 MHz continuum mosaic images with an angular resolution of 6 arcsec (9 arcsec below declination 10$^\circ$) we catalogue 13,667,877 sources, formed from 16,943,656 Gaussian components. The scatter in the astrometric precision approximately follows the expected noise-like behaviour but with an additional systematic component of at least 0.24 arcsec that is likely due to calibration imperfections. The random flux density scale error is 6%, while the systematic offset was previously shown to be within 2%. The median sensitivity of our mosaics is 92$μ$Jy beam$^{-1}$. Completeness simulations, accounting for realistic source models, time- and bandwidth-smearing effects, and astrometric errors, indicate that we detect more than 95% of compact sources with integrated flux densities exceeding 9 times the local root mean square (RMS) noise. However, the recovered source counts in a particular integrated flux density bin do not match the injected counts until flux densities exceed 45 times the local RMS noise. The Euclidean-normalised differential source counts derived from the survey constrain the radio source population over five orders of magnitude and are in good agreement with previous deep and wide-area surveys. All data products are publicly available, including catalogues, individual-field Stokes I, Q, U, and V images, mosaicked Stokes I images, and $uv$ data with associated direction-dependent calibration solutions.

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arXiv2026

Euclid. Properties and performance of the NISP signal estimator

The Euclid spacecraft, located at the second Lagrangian point of the Sun-Earth system, hosts the Near-Infrared Spectrometer and Photometer (NISP) instrument. NISP is equipped with a mosaic of 16 HgCdTe-based detectors to acquire near-infrared photometric and spectroscopic data. To meet the spacecraft's constraints on computational resources and telemetry bandwidth, the near-infrared signal is processed onboard via a dedicated hardware-software architecture designed to fulfil the stringent Euclid's data-quality requirements. A custom application software, running on the two NISP data processing units, implements the NISP signal estimator: an ad-hoc algorithm which delivers accurate flux measurements and simultaneously estimates the quality of signal estimation through the quality factor parameter. This paper investigates the properties of the NISP signal estimator by evaluating its performance during the early flight operations of the NISP instrument. First, we revisit the assumptions on which the inference of the near-infrared signal is based and investigate the origin of the main systematics of the signal estimator through Monte Carlo simulations. Then, we test the flight performance of the NISP signal estimator. Results indicate a systematic bias lower than 0.01 e/s for 99% of the NISP pixel array, well within the noise budget of the estimated signal. We also derive an analytical expression for the variance of the NISP signal estimator, demonstrating its validity, particularly when the covariance matrix is not pre-computed. Finally, we provide a robust statistical framework to interpret the QF parameter, analyse its dependence on the signal estimator bias, and show its sensitivity to cosmic ray hits on NISP detectors. Our findings corroborate previous results on the NISP signal estimator and suggest a leading-order correction based on the agreement between flight data and simulations.

astro-ph.IM↗

arXiv2026

Euclid: Early Release Observations -- The star-formation history of massive early-type galaxies in the Perseus cluster

The Euclid Early Release Observations (ERO) programme targeted the Perseus galaxy cluster in its central region over 0.7deg$^2$. We combined the exceptional image quality and depth of the ERO-Perseus with FUV and NUV observations from GALEX and AstroSat/UVIT, as well as $ugrizHα$ data from MegaCam at the CFHT, to deliver FUV-to-NIR magnitudes of the 87 brightest galaxies within the Perseus cluster. We reconstructed the star-formation history (SFH) of 59 early-type galaxies (ETGs) within the sample, through the spectral energy distribution (SED) fitting code CIGALE and state-of-the-art stellar population (SP) models to reproduce the galactic UV emission from hot, old, low-mass stars (i.e. the UV upturn). In addition, for the six most massive ETGs in Perseus [stellar masses $\log_{10}(M_{\ast}/M_{\odot}) \geq 10.3$], we analysed their spatially resolved SP through a radial SED fitting. In agreement with our previous work on Virgo ETGs, we found that (i) the majority of ETGs needs the presence of an UV upturn to explain their FUV emission, with temperatures $\langle T_{\rm UV}\rangle$~33800 K; (ii) ETGs have grown their stellar masses quickly, with SF timescales $τ\lesssim 1500$ Myr. We found that all ETGs in the sample have formed more than about 30% of their stellar masses at z~5, up to ~100%. At z~5, the stellar masses of the most massive nearby ETGs, which have present-day stellar masses $\log_{10}(M_{\ast}/M_{\odot})\gtrsim 10.8$, are then found to be comparable to those of the red quiescent galaxies observed by JWST at similar redshifts (z>4.6). This study can be extended to ETGs in the 14000 deg$^2$ extragalactic sky that will soon be observed by Euclid, in combination with those from other major upcoming surveys (e.g. Rubin/LSST), and UV observations, to ultimately assess whether the nearby massive ETGs represent the progeny of the massive high-z JWST red quiescent galaxies.

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