arXiv subjects

C. Scarlata

Publications and source records attributed to C. Scarlata.

At least 19 recordsLinked to original sources

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.

astro-ph.CO↗

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.

astro-ph.CO↗

arXiv2026

Witnessing the onset of stellar winds in Super-Luminous Supernova Hosts: implications for star-formation-driven outflows in low and high-redshift galaxies

Direct observational constraints on the earliest, stellar-wind-dominated phases of galactic outflows remain scarce. We present medium-resolution VLT/X-shooter spectroscopy of six Type I superluminous supernova (SLSN-I) host galaxies at z = 0.15-0.51, exploiting the bright SLSN continua as single, down-the-barrel probes of the host interstellar medium. From nebular emission lines we derive dust-corrected star-formation rates as low as 0.06-0.44 Msun yr$^{-1}$, and gas-phase metallicities in the extremely metal-poor regime (less than nine percent solar). Moreover, all hosts exhibit narrow, blueshifted Mg II 2796, 2803 absorption, indicative of the presence of low-ionization outflows along the line of sight. Voigt modeling of the Mg II absorption yields maximum outflow velocities of $v_{max}$ = 37-104 km s$^{-1}$, placing these galaxies systematically below the empirical $v_{max}$-SFR relations for more evolved galaxies of similar SFR. Given the short lifetimes of the SLSN massive progenitors, we argue that these outflows must originate from preceding stellar wind episodes. Assuming a constant-velocity outflow over 3 Myr and spherical symmetry, we infer wind masses M$_{wind}$ = (0.02-1.0) $\times 10^6$ Msun and mass-outflow rates $\dot{M}_{wind} = 0.01-0.33$ Msun yr$^{-1}$, corresponding to mass-loading factors $\eta<1$. These results indicate that, during the first few Myr of a burst, stellar winds and radiation pressure alone drive slow and weak outflows in low-mass systems, prior to the onset of dominant supernova feedback. Our work provides one of the first empirical constraints on early feedback phases relevant for high-redshift galaxies, and for time-dependent implementations of stellar feedback in galaxy formation simulations.

astro-ph.GA↗

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 $\Delta$ z ~ 0.3 lower than that of the SLDE A sample.

astro-ph.GA↗

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.

astro-ph.CO↗

arXiv2025

\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.

gr-qc↗

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.

astro-ph.GA↗

arXiv2025

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

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

astro-ph.CO↗

arXiv2025

Euclid preparation. Simulating thousands of Euclid spectroscopic skies

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

astro-ph.CO↗

arXiv2025

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$\,{\alpha}$ 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$\,{\alpha}$, 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 $f\sigma_8$, $\alpha_{\parallel}$ and $\alpha_{\perp}$ 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 $f\sigma_8$, $\alpha_{\parallel}$, and $\alpha_{\perp}$ 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↗

arXiv2025

The Lyman-alpha and Continuum Origins Survey II: the connection between the escape of ionizing radiation and Lyman-alpha halos in star-forming galaxies

One of the current challenges in galaxy evolution studies is to establish the mechanisms that govern the escape of ionizing radiation from galaxies. Here, we investigate the connection between Lyman Continuum (LyC) escape and the conditions of the Circumgalactic Medium (CGM), as probed by Ly$\alpha$ halos (LAHs) in emission. We use Ly$\alpha$ and UV continuum imaging data from the Lyman alpha and Continuum Origins Survey (LaCOS), targeting 42 nearby ($z \simeq 0.3$), star-forming galaxies with LyC observations (escape fractions of $f_{\rm esc}^{\rm LyC} \simeq 0.01-0.49$). LaCOS galaxies show extended Ly$\alpha$ emission ubiquitously, with LyC emitters (LCEs) having more compact Ly$\alpha$ morphologies than non-LCEs, and Ly$\alpha$ spatial offsets that do not exceed the extent of the UV continuum. We model the diffuse LAHs using a combined S\'ersic plus exponential 2D profile, and find that the characteristic scale length of the Ly$\alpha$ halo is ten times larger than the UV, on average. We unveil a significant anti-correlation between $f_{\rm esc}^{\rm LyC}$ and the Ly$\alpha$ Halo Fraction (HF, or contribution of the halo to the total Ly$\alpha$ luminosity), that we propose as a new LyC indicator. Our observations show that halo scale lengths and HFs both scale positively with the optical depth of the neutral gas in the ISM, revealing a picture in which Ly$\alpha$ and LyC photons in LCEs either emerge directly from the central starbursts or escape isotropically and, in the case of Ly$\alpha$, minimize the number of scattering interactions in a less-extended CGM.

astro-ph.GA↗

arXiv2025

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↗

arXiv2025

Euclid Quick Data Release (Q1), A first look at the fraction of bars in massive galaxies at $z<1$

Stellar bars are key structures in disc galaxies, driving angular momentum redistribution and influencing processes such as bulge growth and star formation. Quantifying the bar fraction as a function of redshift and stellar mass is therefore important for constraining the physical processes that drive disc formation and evolution across the history of the Universe. Leveraging the unprecedented resolution and survey area of the Euclid Q1 data release combined with the Zoobot deep-learning model trained on citizen-science labels, we identify 7711 barred galaxies with $M_* \gtrsim 10^{10}M_\odot$ in a magnitude-selected sample $I_E < 20.5$ spanning $63.1 deg^2$. We measure a mean bar fraction of $0.2-0.4$, consistent with prior studies. At fixed redshift, massive galaxies exhibit higher bar fractions, while lower-mass systems show a steeper decline with redshift, suggesting earlier disc assembly in massive galaxies. Comparisons with cosmological simulations (e.g., TNG50, Auriga) reveal a broadly consistent bar fraction, but highlight overpredictions for high-mass systems, pointing to potential over-efficiency in central stellar mass build-up in simulations. These findings demonstrate Euclid's transformative potential for galaxy morphology studies and underscore the importance of refining theoretical models to better reproduce observed trends. Future work will explore finer mass bins, environmental correlations, and additional morphological indicators.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine E -- Ensemble classification of strong gravitational lenses: lessons for Data Release 1

The Euclid Wide Survey (EWS) is expected to identify of order $100\,000$ galaxy-galaxy strong lenses across $14\,000$deg$^2$. The Euclid Quick Data Release (Q1) of $63.1$deg$^2$ Euclid images provides an excellent opportunity to test our lens-finding ability, and to verify the anticipated lens frequency in the EWS. Following the Q1 data release, eight machine learning networks from five teams were applied to approximately one million images. This was followed by a citizen science inspection of a subset of around $100\,000$ images, of which $65\%$ received high network scores, with the remainder randomly selected. The top scoring outputs were inspected by experts to establish confident (grade A), likely (grade B), possible (grade C), and unlikely lenses. In this paper we combine the citizen science and machine learning classifiers into an ensemble, demonstrating that a combined approach can produce a purer and more complete sample than the original individual classifiers. Using the expert-graded subset as ground truth, we find that this ensemble can provide a purity of $52\pm2\%$ (grade A/B lenses) with $50\%$ completeness (for context, due to the rarity of lenses a random classifier would have a purity of $0.05\%$). We discuss future lessons for the first major Euclid data release (DR1), where the big-data challenges will become more significant and will require analysing more than $\sim300$ million galaxies, and thus time investment of both experts and citizens must be carefully managed.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). The first catalogue of strong-lensing galaxy clusters

We present the first catalogue of strong lensing galaxy clusters identified in the Euclid Quick Release 1 observations (covering $63.1\,\mathrm{deg^2}$). This catalogue is the result of the visual inspection of 1260 cluster fields. Each galaxy cluster was ranked with a probability, $\mathcal{P}_{\mathrm{lens}}$, based on the number and plausibility of the identified strong lensing features. Specifically, we identified 83 gravitational lenses with $\mathcal{P}_{\mathrm{lens}}>0.5$, of which 14 have $\mathcal{P}_{\mathrm{lens}}=1$, and clearly exhibiting secure strong lensing features, such as giant tangential and radial arcs, and multiple images. Considering the measured number density of lensing galaxy clusters, approximately $0.3\,\mathrm{deg}^{-2}$ for $\mathcal{P}_{\mathrm{lens}}>0.9$, we predict that \Euclid\ will likely see more than 4500 strong lensing clusters over the course of the mission. Notably, only three of the identified cluster-scale lenses had been previously observed from space. Thus, \Euclid has provided the first high-resolution imaging for the remaining $80$ galaxy cluster lenses, including those with the highest probability. The identified strong lensing features will be used for training deep-learning models for identifying gravitational arcs and multiple images automatically in \Euclid observations. This study confirms the huge potential of \Euclid for finding new strong lensing clusters, enabling exciting new discoveries on the nature of dark matter and dark energy and the study of the high-redshift Universe.

astro-ph.CO↗

arXiv2025

Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine C: Finding lenses with machine learning

Strong gravitational lensing has the potential to provide a powerful probe of astrophysics and cosmology, but fewer than 1000 strong lenses have been confirmed so far. With a 0.16'' resolution covering a third of the sky, the Euclid telescope will revolutionise the identification of strong lenses, with 170 000 lenses forecasted to be discovered amongst the 1.5 billion galaxies it will observe. We present an analysis of the performance of five machine-learning models at finding strong gravitational lenses in the quick release of Euclid data (Q1) covering 63 deg2. The models have been validated by citizen scientists and expert visual inspection. We focus on the best-performing network: a fine-tuned version of the Zoobot pretrained model originally trained to classify galaxy morphologies in heterogeneous astronomical imaging surveys. Of the one million Q1 objects that Zoobot was tasked to find strong lenses within, the top 1000 ranked objects contain 122 grade A lenses (almost-certain lenses) and 41 grade B lenses (probable lenses). A deeper search with the five networks combined with visual inspection yielded 250 (247) grade A (B) lenses, of which 224 (182) are ranked in the top 20 000 by Zoobot. When extrapolated to the full Euclid survey, the highest ranked one million images will contain 75 000 grade A or B strong gravitational lenses.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1): From spectrograms to spectra: the SIR spectroscopic Processing Function

The Euclid space mission aims to investigate the nature of dark energy and dark matter by mapping the large-scale structure of the Universe. A key component of Euclid's observational strategy is slitless spectroscopy, conducted using the Near Infrared Spectrometer and Photometer (NISP). This technique enables the acquisition of large-scale spectroscopic data without the need for targeted apertures, allowing precise redshift measurements for millions of galaxies. These data are essential for Euclid's core science objectives, including the study of cosmic acceleration and the evolution of galaxy clustering, as well as enabling many non-cosmological investigations. This study presents the SIR processing function (PF), which is responsible for processing slitless spectroscopic data. The objective is to generate science-grade fully-calibrated one-dimensional spectra, ensuring high-quality spectroscopic data. The processing function relies on a source catalogue generated from photometric data, effectively corrects detector effects, subtracts cross-contaminations, minimizes self-contamination, calibrates wavelength and flux, and produces reliable spectra for later scientific use. The first Quick Data Release (Q1) of Euclid's spectroscopic data provides approximately three million validated spectra for sources observed in the red-grism mode from a selected portion of the Euclid Wide Survey. We find that wavelength accuracy and measured resolving power are within requirements, thanks to the excellent optical quality of the instrument. The SIR PF represents a significant step in processing slitless spectroscopic data for the Euclid mission. As the survey progresses, continued refinements and additional features will enhance its capabilities, supporting high-precision cosmological and astrophysical measurements.

astro-ph.IM↗

arXiv2025

Systematic Bias in Ionizing Radiation Escape Fraction Measurements from Foreground Large-Scale Structures

We investigate the relationship between the Lyman-alpha (Lya) forest transmission in the intergalactic medium (IGM) and the environmental density of galaxies, focusing on its implications for the measurement of ionizing radiation escape fractions. Using a sample of 268 spectroscopically confirmed background galaxies at 2.7<z<3.0 and a galaxy density map at z~2.5 within the COSMOS field, we measure the Lya transmission photometrically, leveraging the multiwavelength data available from the COSMOS2020 catalog. Our results reveal a weak but statistically significant positive correlation between Lya optical depth and galaxy density contrast, suggesting that overdense regions are enriched in neutral gas, which could bias escape fraction measurements. This emphasizes the need to account for the large-scale structure of the IGM in analyses of ionizing radiation escape fractions, and highlights the advantages of a photometric approach for increasing the number of sampled lines of sight across large fields. The photometric redshifts provided by upcoming all-sky surveys, such as Euclid, will make it possible to account for this effect across widely separated fields.

astro-ph.GA↗