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C. Tortora

Publications and source records attributed to C. Tortora.

At least 37 records · Page 2Linked to original sources

CASCO: Cosmological and AStrophysical parameters from Cosmological simulations and Observations IV. Testing warm dark matter cosmologies with galaxy scaling relations: A joint simulation-observation study using DREAMS simulations

Small-scale discrepancies in the standard Lambda cold dark matter paradigm have motivated the exploration of alternative dark matter (DM) models, such as warm dark matter (WDM). We investigate the constraining power of galaxy scaling relations on cosmological, astrophysical, and WDM parameters through a joint analysis of hydrodynamic simulations and observational data. Our study is based on the DREAMS project and combines large-volume uniform-box simulations with high-resolution Milky Way zoom-in runs in a $Λ$WDM cosmology. To ensure consistency between the different simulation sets, we apply calibrations to account for resolution effects, allowing us to exploit the complementary strengths of the two suites. We compare simulated relations, including stellar size, DM mass and fraction within the stellar half-mass radius, and the total-to-stellar mass ratio, with two complementary galaxy samples: the SPARC catalog of nearby spirals and the LVDB catalog of dwarf galaxies in the Local Volume. Using a bootstrap-based fitting procedure, we show that key cosmological parameters ($Ω_m$, $σ_8$) and supernova feedback strength can be recovered with good accuracy, particularly from the uniform-box simulations. While the WDM particle mass remains unconstrained, the zoom-in simulations reveal subtle WDM-induced trends at low stellar masses in both the DM mass and total-to-stellar mass ratio. We also find that the galaxy stellar mass function exhibits a measurable dependence on the WDM particle mass below log10(M_*/Msun) <~ 8, which appears separable from the impact of feedback, suggesting it as a promising complementary probe. Our results highlight the importance of combining multi-resolution simulations with diverse observational datasets to jointly constrain baryonic processes and DM properties.

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SHARP: Beyond JWST -- Revealing the galaxy birth and growth with the resolution of the ELT

A deep understanding of the life-cycle of galaxies, particularly those of high mass, requires clarifying the mechanisms that regulate star formation (SF) and its abrupt shutdown (quenching), often capable of stopping SF rates of hundreds of solar masses per year. What initially triggers quenching, and what sustains the quiescent state thereafter, especially given the frequent presence of large gas reservoirs or even massive gas inflows, are unsolved key issues. Ultimately, the crucial connection between the galaxy life-cycle and the surrounding Intergalactic (IGM) and Circumgalactic (CGM) Medium remains largely unclear. Addressing these issues requires studying star formation, chemical enrichment, and quenching homogeneously up to high redshift. The upcoming AO-assisted Extremely Large Telescope (ELT), will deliver sharper and deeper data than the JWST. SHARP is a concept study for a near-IR (0.95-2.45 mu) spectrograph designed to fully exploit the capabilities of ELT. Designed for multi-object slit spectroscopy and multi-Integral Field spectroscopy, SHARP points to achieve angular resolutions (~30 mas) far superior to NIRSpec at JWST(100 mas) to decipher and reconstruct the life-cycle oa galaxies.

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

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

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

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

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Does Machine Learning Work? A Comparative Analysis of Strong Gravitational Lens Searches in the Dark Energy Survey

We present a systematic comparison of three independent machine learning (ML)-based searches for strong gravitational lenses applied to the Dark Energy Survey (Jacobs et al. 2019a,b; Rojas et al. 2022; Gonzalez et al. 2025). Each search employs a distinct ML architecture and training strategy, allowing us to evaluate their relative performance, completeness, and complementarity. Using a visually inspected sample of 1651 systems previously reported as lens candidates, we assess how each model scores these systems and quantify their agreement with expert classifications. The three models show progressive improvement in performance, with F1-scores of 0.31, 0.35, and 0.54 for Jacobs, Rojas, and Gonzalez, respectively. Their completeness for moderate- to high-confidence lens candidates follows a similar trend (31%, 52%, and 70%). When combined, the models recover 82% of all such systems, highlighting their strong complementarity. Additionally, we explore ensemble strategies: average, median, linear regression, decision trees, random forests, and an Independent Bayesian method. We find that all but averaging achieve higher maximum F1 scores than the best individual model, with some ensemble methods improving precision by up to a factor of six. These results demonstrate that combining multiple, diverse ML classifiers can substantially improve the completeness of lens samples while drastically reducing false positives, offering practical guidance for optimizing future ML-based strong lens searches in wide-field surveys.

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Euclid Quick Data Release (Q1). A probabilistic classification of quenched galaxies

Investigating what drives the quenching of star formation in galaxies is key to understanding their evolution. The Euclid mission will provide rich data from optical to infrared wavelengths for millions of galaxies, and enable precise measurements of their star formation histories. Using the first Euclid Quick Data Release (Q1), we developed a probabilistic classification framework that combines the average specific star-formation rate inferred over two timescales ($10^8,10^9$ yr) to categorise galaxies as `ageing' (secularly evolving), `quenched' (recently halted star formation), or `retired' (dominated by old stars). Two classification methods were employed: a probabilistic approach, which integrates posterior distributions, and a model-driven method, which optimises sample purity and completeness using IllustrisTNG. At $z<0.1$ and $M_\ast \gtrsim 3\times10^{8}\,M_\odot$, we obtain Euclid class fractions of 68-72\%, 8-17\%, and 14-19\% for ageing, quenched, and retired populations, respectively. Ageing and retired galaxies dominate at the low- and high-mass end, respectively, while quenched galaxies surpass the retired fraction for $M_\ast \lesssim 10^{10}\,\rm M_\odot$. The evolution with redshift shows increasing and decreasing fractions of ageing and retired galaxies, respectively. More massive galaxies usually undergo quenching episodes at earlier times than to their low-mass counterparts. In terms of the mass-size-metallicity relation, ageing galaxies generally exhibit disc morphologies and low metallicities. Retired galaxies show compact structures and enhanced chemical enrichment, while quenched galaxies form an intermediate population that is more compact and chemically evolved than ageing systems. This work demonstrates Euclid's great potential for elucidating the physical nature of the quenching mechanisms that govern galaxy evolution.

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Euclid Quick Data Release (Q1). First Euclid statistical study of galaxy mergers and their connection to active galactic nuclei

Galaxy major mergers are a key pathway to trigger AGN. We present the first detection of major mergers in the Euclid Deep Fields and analyse their connection with AGN. We constructed a stellar-mass-complete ($M_*>10^{9.8}\,M_{\odot}$) sample of galaxies from the first quick data release (Q1), in the redshift range z=0.5-2. We selected AGN using X-ray data, optical spectroscopy, mid-infrared colours, and processing \IE observations with an image decomposition algorithm. We used CNNs trained on cosmological simulations to classify galaxies as mergers and non-mergers. We found a larger fraction of AGN in mergers compared to the non-merger controls for all AGN selections, with AGN excess factors ranging from 2 to 6. Likewise, a generally larger merger fraction ($f_{merg}$) is seen in active galaxies than in the non-active controls. We analysed $f_{merg}$ as a function of the AGN bolometric luminosity ($L_{bol}$) and the contribution of the point-source to the total galaxy light in the \IE-band ($f_{PSF}$) as a proxy for the relative AGN contribution fraction. We uncovered a rising $f_{merg}$, with increasing $f_{PSF}$ up to $f_{PSF}=0.55$, after which we observed a decreasing trend. We then derived the point-source luminosity ($L_{PSF}$) and showed that $f_{merg}$ monotonically increases as a function of $L_{PSF}$ at z<0.9, with $f_{merg}>$50% for $L_{PSF}>2\,10^{43}$ erg/s. At z>0.9, $f_{merg}$ rises as a function of $L_{PSF}$, though mergers do not dominate until $L_{PSF}=10^{45}$ erg/s. For X-ray and spectroscopic AGN, we computed $L_{bol}$, which has a positive correlation with $f_{merg}$ for X-ray AGN, while shows a less pronounced trend for spectroscopic AGN due to the smaller sample size. At $L_{bol}>10^{45}$ erg/s, AGN mostly reside in mergers. We concluded that mergers are strongly linked to the most powerful, dust-obscured AGN, associated with rapid supermassive black hole growth.

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Euclid Quick Data Release (Q1). Exploring galaxy morphology across cosmic time through Sersic fits

We present the results of the single-component Sérsic profile fitting for the magnitude-limited sample of \IE$<23$ galaxies within the 63.1 deg$^2$ area of the Euclid Quick Data Release (Q1). The associated morphological catalogue includes two sets of structural parameters fitted using \texttt{SourceXtractor++}: one for VIS \IE images and one for a combination of three NISP images in \YE, \JE and \HE bands. We compare the resulting Sérsic parameters to other morphological measurements provided in the Q1 data release, and to the equivalent parameters based on higher-resolution \HST imaging. These comparisons confirm the consistency and the reliability of the fits to Q1 data. Our analysis of colour gradients shows that NISP profiles have systematically smaller effective radii ($R_{\rm e}$) and larger Sérsic indices ($n$) than in VIS. In addition, we highlight trends in NISP-to-VIS parameter ratios with both magnitude and $n_{\rm VIS}$. From the 2D bimodality of the $(u-r)$ colour-$\log(n)$ plane, we define a $(u-r)_{\rm lim}(n)$ that separates early- and late-type galaxies (ETGs and LTGs). We use the two subpopulations to examine the variations of $n$ across well-known scaling relations at $z<1$. ETGs display a steeper size--stellar mass relation than LTGs, indicating a difference in the main drivers of their mass assembly. Similarly, LTGs and ETGs occupy different parts of the stellar mass--star-formation rate plane, with ETGs at higher masses than LTGs, and further down below the Main Sequence of star-forming galaxies. This clear separation highlights the link known between the shutdown of star formation and morphological transformations in the Euclid imaging data set. In conclusion, our analysis demonstrates both the robustness of the Sérsic fits available in the Q1 morphological catalogue and the wealth of information they provide for studies of galaxy evolution with Euclid.

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Euclid: Early Release Observations -- Interplay between dwarf galaxies and their globular clusters in the Perseus galaxy cluster

We present an analysis of globular clusters (GCs) of dwarf galaxies in the Perseus galaxy cluster to explore the relationship between dwarf galaxy properties and their GCs. Our focus is on GC numbers ($N_{\rm GC}$) and GC half-number radii ($R_{\rm GC}$) around dwarf galaxies, and their relations with host galaxy stellar masses ($M_*$), central surface brightnesses ($μ_0$), and effective radii ($R_{\rm e}$). Interestingly, we find that at a given stellar mass, $R_{\rm GC}$ is almost independent of the host galaxy $μ_0$ and $R_{\rm e}$, while $R_{\rm GC}/R_{\rm e}$ depends on $μ_0$ and $R_{\rm e}$; lower surface brightness and diffuse dwarf galaxies show $R_{\rm GC}/R_{\rm e}\approx 1$ while higher surface brightness and compact dwarf galaxies show $R_{\rm GC}/R_{\rm e}\approx 1.5$-$2$. This means that for dwarf galaxies of similar stellar mass, the GCs have a similar median extent; however, their distribution is different from the field stars of their host. Additionally, low surface brightness and diffuse dwarf galaxies on average have a higher $N_{\rm GC}$ than high surface brightness and compact dwarf galaxies at any given stellar mass. We also find that UDGs (ultra-diffuse galaxies) and non-UDGs have similar $R_{\rm GC}$, while UDGs have smaller $R_{\rm GC}/R_{\rm e}$ (typically less than 1) and 3-4 times higher $N_{\rm GC}$ than non-UDGs. Examining nucleated and not-nucleated dwarf galaxies, we find that for $M_*>10^8M_{\odot}$, nucleated dwarf galaxies seem to have smaller $R_{\rm GC}$ and $R_{\rm GC}/R_{\rm e}$, with no significant differences between their $N_{\rm GC}$, except at $M_*<10^8M_{\odot}$ where the nucleated dwarf galaxies tend to have a higher $N_{\rm GC}$. Lastly, we explore the stellar-to-halo mass ratio (SHMR) of dwarf galaxies and conclude that the Perseus cluster dwarf galaxies follow the expected SHMR at $z=0$ extrapolated down to $M_*=10^6M_{\odot}$.

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Euclid preparation. Spatially resolved stellar populations of local galaxies with Euclid: a proof of concept using synthetic images with the TNG50 simulation

The European Space Agency's Euclid mission will observe approximately 14,000 $\rm{deg}^{2}$ of the extragalactic sky and deliver high-quality imaging for many galaxies. The depth and high spatial resolution of the data will enable a detailed analysis of stellar population properties of local galaxies. In this study, we test our pipeline for spatially resolved SED fitting using synthetic images of Euclid, LSST, and GALEX generated from the TNG50 simulation. We apply our pipeline to 25 local simulated galaxies to recover their resolved stellar population properties. We produce 3 types of data cubes: GALEX + LSST + Euclid, LSST + Euclid, and Euclid-only. We perform the SED fitting tests with two SPS models in a Bayesian framework. Because the age, metallicity, and dust attenuation estimates are biased when applying only classical formulations of flat priors, we examine the effects of additional priors in the forms of mass-age-$Z$ relations, constructed using a combination of empirical and simulated data. Stellar-mass surface densities can be recovered well using any of the 3 data cubes, regardless of the SPS model and prior variations. The new priors then significantly improve the measurements of mass-weighted age and $Z$ compared to results obtained without priors, but they may play an excessive role compared to the data in determining the outcome when no UV data is available. The spatially resolved SED fitting method is powerful for mapping the stellar populations of galaxies with the current abundance of high-quality imaging data. Our study re-emphasizes the gain added by including multiwavelength data from ancillary surveys and the roles of priors in Bayesian SED fitting. With the Euclid data alone, we will be able to generate complete and deep stellar mass maps of galaxies in the local Universe, thus exploiting the telescope's wide field, NIR sensitivity, and high spatial resolution.

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CASCO: Cosmological and AStrophysical parameters from Cosmological simulations and Observations III. The physics behind the emergence of the golden mass scale

We investigate the origin and evolution of the "golden mass" (halo mass $\sim10^{12} \, \rm M_{\odot}$, stellar mass $\sim5 \times 10^{10} \, \rm M_{\odot}$), linked to peak star formation efficiency, using \textsc{camels} simulations based on IllustrisTNG. Exploring a range of SN/AGN feedback strengths and cosmologies ($Ω_{\rm m}, σ_8$), we find a U-shaped relation between dark-to-stellar mass ratio and stellar mass, with a minimum at the golden mass, in line with observations. Cosmology affects the normalization of this relation, while feedback shapes its form and the emergence of the golden mass. Stronger SN feedback lowers its value; AGN feedback, especially radiative efficiency, alters the high-mass slope and shifts the golden mass. The golden mass appears earlier with stronger feedback, which quenches star formation more rapidly. Passive galaxies retain the U-shape; star-forming ones show decreasing dark matter fraction with stellar mass, with possible reversal at low redshift. Global stellar fractions also exhibit a U-shaped trend: in passive galaxies, the golden mass shifts to lower masses or vanishes; in star-forming ones, it emerges only at low redshift. Feedback governs the golden mass up to $z \sim 1.5-2$, with a secondary role from cold streams and virial shocks. We speculate that at $z \gtrsim 1.5-2$, a single stream-regulated scale governs galaxy growth, which later bifurcates into two: a low-mass scale tied to gas richness and a higher-mass golden mass regulating efficiency and quenching. (abridged)

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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.

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From simulations to observations. Methodology and data release of mock TNG50 galaxies at 0.3 < z < 0.7 for WEAVE-StePS

The new generation of optical spectrographs (i.e., WEAVE, 4MOST, DESI, and WST) offer unprecedented opportunities for statistically studying the star formation histories of galaxies. However, these observations are not easily comparable to predictions from cosmological simulations. Our goal is to build a reference framework for comparing spectroscopic observations with simulations and test tools for deriving stellar population properties of galaxies. We focus on the observational strategy of the Stellar Population at Intermediate Redshift Survey (StePS) with the WEAVE instrument. We generate mock datasets of ~750 galaxies at redshifts z = 0.3, 0.5, and 0.7 using the TNG50 simulation, perform radiative transfer with SKIRT, and analyze the spectra with pPXF as if they were real observations. We present the methodology to generate these datasets and provide an initial exploration of stellar population parameters (i.e., mass-weighted ages and metallicities) and star formation histories for three galaxies at z = 0.7 and their descendants at z = 0.5 and 0.3. We find good agreement between the mock spectra and intrinsic ages in TNG50 (average difference $0.2\pm0.3$ Gyr) and successfully recover their star formation histories, especially for galaxies form the bulk of their stars on short timescales and at early epochs. We release these datasets, including multi-wavelength imaging and spectra, to support forthcoming WEAVE observations.

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Euclid: Early Release Observations -- The surface brightness and colour profiles of the far outskirts of galaxies in the Perseus cluster

The Perseus field captured by Euclid as part of its Early Release Observations provides a unique opportunity to study cluster environment ranging from outskirts to dense regions. Leveraging unprecedented optical and near-infrared depths, we investigate the stellar structure of massive disc galaxies in this field. This study focuses on outer disc profiles, including simple exponential (Type I), down- (Type II) and up-bending break (Type III) profiles, and their associated colour gradients, to trace late assembly processes across various environments. Type II profiles, though relatively rare in high dense environments, appear stabilised by internal mechanisms like bars and resonances, even within dense cluster cores. Simulations suggest that in dense environments, Type II profiles tend to evolve into Type I profiles over time. Type III profiles often exhibit small colour gradients beyond the break, hinting at older stellar populations, potentially due to radial migration or accretion events. We analyse correlations between galaxy mass, morphology, and profile types. Mass distributions show weak trends of decreasing mass from the centre to the outskirts of the Perseus cluster. Type III profiles become more prevalent, while Type I profiles decrease in lower-mass galaxies with cluster centric distance. Type I profiles dominate in spiral galaxies, while Type III profiles are more common in S0 galaxies. Type II profiles are consistently observed across all morphological types. While the limited sample size restricts statistical power, our findings shed light on the mechanisms shaping galaxy profiles in cluster environments. Future work should extend observations to the cluster outskirts to enhance statistical significance. Additionally, 3D velocity maps are needed to achieve a non-projected view of galaxy positions, offering deeper insights into spatial distribution and dynamics.

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INSPIRE: INvestigating Stellar Populations In RElics. IX. KiDS J0842+0059: the first fully confirmed relic beyond the local Universe

Relics are massive, compact and quiescent galaxies that assembled the majority of their stars in the early Universe and lived untouched until today, completely missing any subsequent size-growth caused by mergers and interactions. They provide the unique opportunity to put constraints on the first phase of mass assembly in the Universe with the ease of being nearby. While only a few relics have been found in the local Universe, the {\tt INSPIRE} project has confirmed 38 relics at higher redshifts ($z \sim 0.2-0.4$), fully characterising their integrated kinematics and stellar populations. However, given the very small sizes of these objects and the limitations imposed by the atmosphere, structural parameters inferred from ground-based optical imaging are possibly affected by systematic effects that are difficult to quantify. In this paper, we present the first high-resolution image obtained with Adaptive Optics Ks-band observations on SOUL-LUCI@LBT of one of the most extreme {\tt INSPIRE} relics, KiDS~J0842+0059 at $z \sim 0.3$. We confirm the disky morphology of this galaxy (axis ratio of $0.24$) and its compact nature (circularized effective radius of $\sim 1$ kpc) by modelling its 2D surface brightness profile with a PSF-convolved Sérsic model. We demonstrate that the surface mass density profile of KiDS~J0842+0059 closely resembles that of the most extreme local relic, NGC~1277, as well as of high-redshift red nuggets. We unambiguously conclude that this object is a remnant of a high-redshift compact and massive galaxy, which assembled all of its mass at $z>2$, and completely missed the merger phase of the galaxy evolution.

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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., Sérsic 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.

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Euclid: The Early Release Observations Lens Search Experiment

We investigated the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we performed a systematic visual inspection of the $0.7\,\rm{deg}^2$ Euclid Early Release Observations data towards the Perseus cluster using both the high-resolution $I_{\scriptscriptstyle\rm E}$ band and the lower-resolution $Y_{\scriptscriptstyle\rm E}$, $J_{\scriptscriptstyle\rm E}$, $H_{\scriptscriptstyle\rm E}$ bands. Each extended source brighter than magnitude 23 in $I_{\scriptscriptstyle\rm E}$ was inspected by 41 expert human classifiers. This amounts to $12\,086$ stamps of $10^{\prime\prime}\,\times\,10^{\prime\prime}$. We found $3$ grade A and $13$ grade B candidates. We assessed the validity of these $16$ candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling, and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full $14\,000\,{\rm deg}^2$ of the Euclid Wide Survey should contain $100\,000^{+70\,000}_{-30\,000}$ galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of $170\,000$ discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range $0.\!\!^{\prime\prime}68\,<\,θ_\mathrm{E}\,<1.\!\!^{\prime\prime}24$, but their Einstein radius distribution is on the higher side when compared to theoretical forecasts. This suggests that our methodology is likely missing small-Einstein-radius systems. Whilst it is implausible to visually inspect the full Euclid dataset, our results corroborate the promise that Euclid will ultimately deliver a sample of around $10^5$ galaxy-scale lenses.

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Euclid preparation. Estimating galaxy physical properties using CatBoost chained regressors with attention

Euclid will image ~14000 deg^2 of the extragalactic sky at visible and NIR wavelengths, providing a dataset of unprecedented size and richness that will facilitate a multitude of studies into the evolution of galaxies. In the vast majority of cases the main source of information will come from broad-band images and data products thereof. Therefore, there is a pressing need to identify or develop scalable yet reliable methodologies to estimate the redshift and physical properties of galaxies using broad-band photometry from Euclid, optionally including ground-based optical photometry also. To address this need, we present a novel method to estimate the redshift, stellar mass, star-formation rate, specific star-formation rate, E(B-V), and age of galaxies, using mock Euclid and ground-based photometry. The main novelty of our property-estimation pipeline is its use of the CatBoost implementation of gradient-boosted regression-trees, together with chained regression and an intelligent, automatic optimization of the training data. The pipeline also includes a computationally-efficient method to estimate prediction uncertainties, and, in the absence of ground-truth labels, provides accurate predictions for metrics of model performance up to z~2. We apply our pipeline to several datasets consisting of mock Euclid broad-band photometry and mock ground-based ugriz photometry, to evaluate the performance of our methodology for estimating the redshift and physical properties of galaxies detected in the Euclid Wide Survey. The quality of our photometric redshift and physical property estimates are highly competitive overall, validating our modeling approach. We find that the inclusion of ground-based optical photometry significantly improves the quality of the property estimation, highlighting the importance of combining Euclid data with ancillary ground-based optical data. (Abridged)

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