arXiv subjects

S. Quai

Publications and source records attributed to S. Quai.

6 recordsLinked to original sources

arXiv2025

Euclid Quick Data Release (Q1). Quenching precedes bulge formation in dense environments but follows it in the field

(Abridged) The bimodality between star-forming discs and quiescent spheroids requires the existence of two main processes: the galaxy quenching and the morphological transformation. In this paper, we aim to understand the link between these processes and their relation with the stellar mass of galaxies and their local environment. Taking advantage of the first data released by the Euclid Collaboration, covering more than 60 deg2 with space-based imaging and photometry, we analyse a mass-complete sample of nearly one million galaxies in the range 0.25 10^{9.5} M_\odot$. We divide the sample into four sub-populations of galaxies, based on their star-formation activity and morphology. We then analyse the physical properties of these populations and their relative abundances in the stellar mass vs. local density plane. Together with confirming the passivity-density relation and the morphology-density relation, we find that quiescent discy galaxies are more abundant in the low-mass regime of high-density environment. At the same time, star-forming bulge-dominated galaxies are more common in field regions, preferentially at high masses. Building on these results and interpreting them through comparison with simulations, we propose a scenario where the evolution of galaxies in the field significantly differs from that in higher-density environments. The morphological transformation in the majority of field galaxies takes place before the onset of quenching and is mainly driven by secular processes taking place within the main sequence, leading to the formation of star-forming bulge-dominated galaxies as intermediate-stage galaxies. Conversely, quenching of star formation precedes morphological transformation for most galaxies in higher-density environments. This causes the formation of quiescent disc-dominated galaxies before their transition into bulge-dominated ones.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). Spectroscopic unveiling of highly ionised lines at z = 2.48-3.88

This study explores a rare population of sources in a currently uncharted region of spectroscopic redshift space in the Euclid Quick Data Release (Q1), and is intended potentially to support upcoming spectroscopic studies. Our goal is to identify and investigate a population of sources characterised by highly ionised emission lines in their spectra, which are indicative of active galactic nucleus activity, extreme shock phenomena, or Wolf--Rayet stars. A comprehensive visual inspection of spectra is conducted to ensure the reliability of the sample, focusing on the simultaneous detection of both NeV and OII emission-line measurements, a condition that restricts the Euclid spectroscopic redshift range to z=2.48--3.88. To characterise this population, we analysed the morpho-spectrophotometric properties of their host galaxies. This allowed for a direct comparison with control sources that exhibit similar OII properties and spectroscopic redshifts, but not NeV lines. We identify sources solely based on spectroscopic criteria in the redshift range beyond the Halpha regime. Encompassing 65 potential NeV candidates, the resulting sample delivers the first systematic probe of these NeV candidate emitters at high redshift. We found a good agreement, within 1$\sigma$, between the spectral measurements calculated using both direct integration and Gaussian fitting methodologies. The NeV candidates exhibit colours similar to bright QSOs, with only a few in the tail of very red quasars. We observed a higher stellar mass content, a lower continuum around the 4000A break, and a similar S\'{e}rsic index distribution compared to the control sample. This unique sample paves the way for a wide range of scientific investigations, which will be pursued in the forthcoming data releases.

astro-ph.GA↗

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 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 view of the star-forming main sequence in the Euclid Deep Fields

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

astro-ph.GA↗

arXiv2024

Euclid preparation. LI. Forecasting the recovery of galaxy physical properties and their relations with template-fitting and machine-learning methods

Euclid will collect an enormous amount of data during the mission's lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting methods, numerous machine learning algorithms have been presented for computing their photometric redshifts and physical parameters (PPs), requiring significantly less computing effort while producing equivalent performance measures. However, their performance is limited by the quality and amount of input information, to the point where the recovery of some well-established physical relationships between parameters might not be guaranteed. To forecast the reliability of Euclid photo-$z$s and PPs calculations, we produced two mock catalogs simulating Euclid photometry. We simulated the Euclid Wide Survey (EWS) and Euclid Deep Fields (EDF). We tested the performance of a template-fitting algorithm (Phosphoros) and four ML methods in recovering photo-$z$s, PPs (stellar masses and star formation rates), and the SFMS. To mimic the Euclid processing as closely as possible, the models were trained with Phosphoros-recovered labels. For the EWS, we found that the best results are achieved with a mixed labels approach, training the models with wide survey features and labels from the Phosphoros results on deeper photometry, that is, with the best possible set of labels for a given photometry. This imposes a prior, helping the models to better discern cases in degenerate regions of feature space, that is, when galaxies have similar magnitudes and colors but different redshifts and PPs, with performance metrics even better than those found with Phosphoros. We found no more than 3% performance degradation using a COSMOS-like reference sample or removing u band data, which will not be available until after data release DR1. The best results are obtained for the EDF, with appropriate recovery of photo-$z$, PPs, and the SFMS.

astro-ph.GA↗