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R. Gavazzi

Publications and source records attributed to R. Gavazzi.

At least 37 records · Page 2Linked to original sources

CHEX-MATE: Multi-probe analysis of Abell 1689

The nature of the elusive dark matter can be probed by comparing the predictions of the cold dark matter framework with the gravitational field of massive galaxy clusters. However, a robust test of dark matter can only be achieved if the systematic uncertainties in the reconstruction of the gravitational potential are minimized. Techniques based on the properties of intracluster gas rely on the assumption that the gas is in hydrostatic equilibrium within the potential well, whereas gravitational lensing is sensitive to projection effects. Here we attempt to minimize systematics in galaxy cluster mass reconstructions by jointly exploiting the weak gravitational lensing signal and the properties of the hot intracluster gas determined from X-ray and millimeter (Sunyaev-Zel'dovich) observations. We construct a model to fit the multi-probe information within a common framework, accounting for non-thermal pressure support and elongation of the dark matter halo along the line of sight. We then apply our framework to the massive cluster Abell 1689, which features unparalleled multi-wavelength data. In accordance with previous works, we find that the cluster is significantly elongated along the line of sight. Accounting for line-of-sight projections, we require a non-thermal pressure support of $30\text{-}40\%$ at $r_{500}$ to match the gas and weak lensing observables. The joint model retrieves a concentration $c_{200}\sim7$, which is lower and more realistic than the high concentration retrieved from weak lensing data alone under the assumption of spherical symmetry ($c_{200}\sim15$). Application of our method to a larger sample will allow us to study at the same time the shape of dark matter mass profiles and the level of non-thermal pressure support in galaxy clusters.

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Euclid Quick Data Release (Q1): The Strong Lensing Discovery Engine A -- System overview and lens catalogue

We present a catalogue of 497 galaxy-galaxy strong lenses in the Euclid Quick Release 1 data (63 deg$^2$). In the initial 0.45\% of Euclid's surveys, we double the total number of known lens candidates with space-based imaging. Our catalogue includes 250 grade A candidates, the vast majority of which (243) were previously unpublished. Euclid's resolution reveals rare lens configurations of scientific value including double-source-plane lenses, edge-on lenses, complete Einstein rings, and quadruply-imaged lenses. We resolve lenses with small Einstein radii ($θ_{\rm E} < 1''$) in large numbers for the first time. These lenses are found through an initial sweep by deep learning models, followed by Space Warps citizen scientist inspection, expert vetting, and system-by-system modelling. Our search approach scales straightforwardly to Euclid Data Release 1 and, without changes, would yield approximately 7000 high-confidence (grade A or B) lens candidates by late 2026. Further extrapolating to the complete Euclid Wide Survey implies a likely yield of over 100000 high-confidence candidates, transforming strong lensing science.

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Euclid Quick Data Release (Q1) The Strong Lensing Discovery Engine B -- Early strong lens candidates from visual inspection of high velocity dispersion galaxies

We present a search for strong gravitational lenses in Euclid imaging with high stellar velocity dispersion ($σ_ν> 180$ km/s) reported by SDSS and DESI. We performed expert visual inspection and classification of $11\,660$ \Euclid images. We discovered 38 grade A and 40 grade B candidate lenses, consistent with an expected sample of $\sim$32. Palomar spectroscopy confirmed 5 lens systems, while DESI spectra confirmed one, provided ambiguous results for another, and help to discard one. The \Euclid automated lens modeler modelled 53 candidates, confirming 38 as lenses, failing to model 9, and ruling out 6 grade B candidates. For the remaining 25 candidates we could not gather additional information. More importantly, our expert-classified non-lenses provide an excellent training set for machine learning lens classifiers. We create high-fidelity simulations of \Euclid lenses by painting realistic lensed sources behind the expert tagged (non-lens) luminous red galaxies. This training set is the foundation stone for the \Euclid galaxy-galaxy strong lensing discovery engine.

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Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine D -- Double-source-plane lens candidates

Strong gravitational lensing systems with multiple source planes are powerful tools for probing the density profiles and dark matter substructure of the galaxies. The ratio of Einstein radii is related to the dark energy equation of state through the cosmological scaling factor $β$. However, galaxy-scale double-source-plane lenses (DSPLs) are extremely rare. In this paper, we report the discovery of four new galaxy-scale double-source-plane lens candidates in the Euclid Quick Release 1 (Q1) data. These systems were initially identified through a combination of machine learning lens-finding models and subsequent visual inspection from citizens and experts. We apply the widely-used {\tt LensPop} lens forecasting model to predict that the full \Euclid survey will discover 1700 DSPLs, which scales to $6 \pm 3$ DSPLs in 63 deg$^2$, the area of Q1. The number of discoveries in this work is broadly consistent with this forecast. We present lens models for each DSPL and infer their $β$ values. Our initial Q1 sample demonstrates the promise of \Euclid to discover such rare objects.

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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.

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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.

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Euclid: Early Release Observations -- The Intracluster Light of Abell 2390

Intracluster light (ICL) provides a record of the dynamical interactions undergone by clusters, giving clues on cluster formation and evolution. Here, we analyse the properties of ICL in the massive cluster Abell 2390 at redshift z=0.228. Our analysis is based on the deep images obtained by the Euclid mission as part of the Early Release Observations in the near-infrared (Y, J, H bands), using the NISP instrument in a 0.75 deg$^2$ field. We subtracted a point--spread function (PSF) model and removed the Galactic cirrus contribution in each band after modelling it with the DAWIS software. We then applied three methods to detect, characterise, and model the ICL and the brightest cluster galaxy (BCG): the CICLE 2D multi-galaxy fitting; the DAWIS wavelet-based multiscale software; and a mask-based 1D profile fitting. We detect ICL out to 600 kpc. The ICL fractions derived by our three methods range between 18% and 36% (average of 24%), while the BCG+ICL fractions are between 21% and 41% (average of 29%), depending on the band and method. A galaxy density map based on 219 selected cluster members shows a strong cluster substructure to the south-east and a smaller feature to the north-west. Based on colours, the ICL (out to about 400 kpc) seems to be built by the accretion of small systems (M ~ $10^{9.5}$ solar mass), or from stars coming from the outskirts of Milky Way-type galaxies (M ~ $10^{10}$ solar mass). Though Abell 2390 does not seem to be undergoing a merger, it is not yet fully relaxed, since it has accreted two groups that have not fully merged with the cluster core. We estimate that the contributions to the inner 300 kpc of the ICL of the north-west and south-east subgroups are 21% and 9% respectively.

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CHEX-MATE: Scaling relations of radio halo profiles for clusters in the LoTSS DR2 area

The thermal and non-thermal components in galaxy clusters have properties that, although shaped from different physical phenomena, can share some similarities, mainly driven by their halo mass and the accretion processes. Scaling relations have been proven to exist for both components and studied in X-ray (thermal) and radio (non-thermal) bands. At the radio wavelength, such investigations are so far limited to the integrated quantities (e.g. total power and mass). We aimed to investigate the scaling relations between the mass of a galaxy cluster and its radio emission at low frequencies, treating both the integrated and the spatially resolved quantities for a sample of well-selected targets. We crossmatched LoTSS DR2 and CHEX-MATE datasets in order to get the deepest and most homogeneous radio data of a representative sample of objects. We analytically derived the expected relation between the radio power ($P_ν$) and radio surface brightness profile, and performed a comparison with observational results. We obtained that properly accounting for the mass and redshift dependence in the radio profile can reduce the overall scatter by a factor of $\sim 4$, with an evident residual dependence on the cluster dynamical status. We showed that assuming no relation between the halo size ($R_{H}$) and the cluster mass ($M$) allowed us to reconcile the observed radio profile mass scaling and the one predicted starting from the $P_ν-M$ relation. We discuss the implications of a lack of $R_H-M$ relation, assessing possible systematics and biases in the analyses, and interpreting it as a natural consequence of the structure formation process. Finally, we also considered the role of the magnetic field in the $P_ν-M$ relation, putting constraints on its dependence upon the cluster mass and finding consistent results with expectations from our radio power mass scaling.

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Euclid: Finding strong gravitational lenses in the Early Release Observations using convolutional neural networks

The Early Release Observations (ERO) from Euclid have detected several new galaxy-galaxy strong gravitational lenses, with the all-sky survey expected to find 170,000 new systems, greatly enhancing studies of dark matter, dark energy, and constraints on the cosmological parameters. As a first step, visual inspection of all galaxies in one of the ERO fields (Perseus) was carried out to identify candidate strong lensing systems and compared to the predictions from Convolutional Neural Networks (CNNs). However, the entire ERO data set is too large for expert visual inspection. In this paper, we therefore extend the CNN analysis to the whole ERO data set, using different CNN architectures and methodologies. Using five CNN architectures, we identified 8,469 strong gravitational lens candidates from IE-band cutouts of 13 Euclid ERO fields, narrowing them to 97 through visual inspection, including 14 grade A and 31 grade B candidates. We present the spectroscopic confirmation of a strong gravitational lensing candidate, EUCLJ081705.61+702348.8. The foreground lensing galaxy, an early-type system at redshift z = 0.335, and the background source, a star-forming galaxy at redshift z = 1.475 with [O II] emission, are both identified. Lens modeling using the Euclid strong lens modeling pipeline reveals two distinct arcs in a lensing configuration, with an Einstein radius of 1.18 \pm 0.03 arcseconds, confirming the lensing nature of the system. These findings highlight the importance of a broad CNN search to efficiently reduce candidates, followed by visual inspection to eliminate false positives and achieve a high-purity sample of strong lenses in Euclid.

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Euclid: A complete Einstein ring in NGC 6505

We report the discovery of a complete Einstein ring around the elliptical galaxy NGC 6505, at $z=0.042$. This is the first strong gravitational lens discovered in Euclid and the first in an NGC object from any survey. The combination of the low redshift of the lens galaxy, the brightness of the source galaxy ($I_\mathrm{E}=18.1$ lensed, $I_\mathrm{E}=21.3$ unlensed), and the completeness of the ring make this an exceptionally rare strong lens, unidentified until its observation by Euclid. We present deep imaging data of the lens from the Euclid Visible Camera (VIS) and Near-Infrared Spectrometer and Photometer (NISP) instruments, as well as resolved spectroscopy from the Keck Cosmic Web Imager (KCWI). The Euclid imaging in particular presents one of the highest signal-to-noise ratio optical/near-infrared observations of a strong gravitational lens to date. From the KCWI data we measure a source redshift of $z=0.406$. Using data from the Dark Energy Spectroscopic Instrument (DESI) we measure a velocity dispersion for the lens galaxy of $σ_\star=303\pm15\,\mathrm{kms}^{-1}$. We model the lens galaxy light in detail, revealing angular structure that varies inside the Einstein ring. After subtracting this light model from the VIS observation, we model the strongly lensed images, finding an Einstein radius of 2.5 arcsec, corresponding to $2.1\,\mathrm{kpc}$ at the redshift of the lens. This is small compared to the effective radius of the galaxy, $R_\mathrm{eff}\sim 12.3\,\mathrm{arcsec}$. Combining the strong lensing measurements with analysis of the spectroscopic data we estimate a dark matter fraction inside the Einstein radius of $f_\mathrm{DM} = (11.1_{-3.5}^{+5.4})\%$ and a stellar initial mass-function (IMF) mismatch parameter of $α_\mathrm{IMF} = 1.26_{-0.08}^{+0.05}$, indicating a heavier-than-Chabrier IMF in the centre of the galaxy.

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Radio emission from a massive node of the cosmic web. A discovery powered by machine learning

Aims. We aim to understand the nature of the diffuse radio emission surrounding the massive galaxy cluster PSZ2 G083.29-31.03, at z=0.412, already known to host a radio halo. Our investigation was triggered by Radio U-Net, a novel machine learning algorithm for detecting diffuse radio emission, which was previously applied to the LOFAR Two Meter Sky Survey (LoTSS). Methods. We re-processed LoTSS (120-168 MHz) data and analyzed archival XMM-Newton (0.7-1.2 keV) observations. We also analyzed optical and near-infrared data from the DESI Legacy Imaging Surveys and asses the mass distribution with weak-lensing analysis based on archival Subaru Suprime-Cam and CFHT MegaPrime/MegaCam observations. Results. We report the discovery of large-scale diffuse radio emission around PSZ2 G083.29-31.03, with a projected largest linear size of 5 Mpc at 144 MHz. The radio emission is aligned with the thermal X-ray emission and the distribution of galaxies, unveiling the presence of two low-mass systems, at similar redshifts on either side of the central cluster. The weak lensing analysis supports this scenario, demonstrating the presence of an extended and complex mass distribution. Conclusions. We propose to interpret the two faint radio sources as connected to the central cluster, thus illuminating the presence of two substructures merging into a massive node of the cosmic web. However, because of uncertainties in redshift and mass estimates, combined with the low resolution required to detect these sources, the classification of the two sources as independent radio halos associated with nearby low-mass clusters or even as a mixture of different types of diffuse radio emission cannot be definitively ruled out.

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Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field

The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg^2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientists alone is infeasible. Machine learning algorithms, particularly convolutional neural networks (CNNs), have been used as an automated method of detecting strong lenses, and have proven fruitful in finding galaxy-galaxy strong lens candidates. We identify the major challenge to be the automatic detection of galaxy-galaxy strong lenses while simultaneously maintaining a low false positive rate. One aim of this research is to have a quantified starting point on the achieved purity and completeness with our current version of CNN-based detection pipelines for the VIS images of EWS. We select all sources with VIS IE < 23 mag from the Euclid Early Release Observation imaging of the Perseus field. We apply a range of CNN architectures to detect strong lenses in these cutouts. All our networks perform extremely well on simulated data sets and their respective validation sets. However, when applied to real Euclid imaging, the highest lens purity is just 11%. Among all our networks, the false positives are typically identifiable by human volunteers as, for example, spiral galaxies, multiple sources, and artefacts, implying that improvements are still possible, perhaps via a second, more interpretable lens selection filtering stage. There is currently no alternative to human classification of CNN-selected lens candidates. Given the expected 10^5 lensing systems in Euclid, this implies 10^6 objects for human classification, which while very large is not in principle intractable and not without precedent.

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CHEX-MATE: the intracluster medium entropy distribution in the gravity-dominated regime

We characterise the entropy profiles of 32 very high mass ($M_{500}>7.75\times10^{14}~M_{\odot}$) galaxy clusters (HIGHMz), selected from the CHEX-MATE sample, to study the intracluster medium (ICM) entropy distribution in a regime where non-gravitational effects are minimised. Using XMM-Newton measurements, we measure the entropy profiles up to ~$R_{500}$ for all objects. The scaled profiles exhibit large dispersion in the central regions, but converge rapidly to the expectation from pure gravitational collapse beyond the core. We quantify the correlation between the ICM morphological parameters and scaled entropy as a function of radius, showing that morphologically relaxed (disturbed) objects have low (high) central entropy. We compare our data to other observational samples, finding differences in normalisation which are linked to the average mass of the samples in question. We find that a weaker mass dependence than self-similar in the scaling (Am ~ -0.25) allows us to minimise the dispersion in the radial range [0.3-0.8]$R_{500}$ for clusters spanning over a decade in mass. The deviation from self-similarity is radially dependent and is more pronounced at small and intermediate radii than at $R_{500}$. We also investigate the distribution of central entropy $K_0$, finding no evidence for bimodality, and outer slopes $α$, which peaks at ~1.1. Using weak lensing masses, we find indication for a small suppression of the scatter (~30%) beyond the core when using masses derived from Yx in the rescaling. Finally, we compare to recent cosmological numerical simulations from THE THREE HUNDRED and MACSIS, finding good agreement with our observational data. These results provide a robust observational benchmark in the gravity-dominated regime and will serve as a future reference for samples at lower mass, higher redshifts, and for ongoing work using cosmological numerical simulations.

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Euclid: Early Release Observations -- A preview of the Euclid era through a galaxy cluster magnifying lens

We present the first analysis of the Euclid Early Release Observations (ERO) program that targets fields around two lensing clusters, Abell 2390 and Abell 2764. We use VIS and NISP imaging to produce photometric catalogs for a total of $\sim 500\,000$ objects. The imaging data reach a $5\,σ$ typical depth in the range 25.1-25.4 AB in the NISP bands, and 27.1-27.3 AB in the VIS band. Using the Lyman-break method in combination with photometric redshifts, we identify $30$ Lyman-break galaxy (LBG) candidates at $z>6$ and 139 extremely red sources (ERSs), most likely at lower redshift. The deeper VIS imaging compared to NISP means we can routinely identify high-redshift Lyman breaks of the order of $3$ magnitudes, which reduces contamination by brown dwarf stars and low-redshift galaxies. Spectroscopic follow-up campaigns of such bright sources will help constrain both the bright end of the ultraviolet galaxy luminosity function and the quasar luminosity function at $z>6$, and constrain the physical nature of these objects. Additionally, we have performed a combined strong lensing and weak lensing analysis of A2390, and demonstrate how Euclid will contribute to better constraining the virial mass of galaxy clusters. From these data, we also identify optical and near-infrared counterparts of known $z>0.6$ clusters, which exhibit strong lensing features, establishing the ability of Euclid to characterize high-redshift clusters. Finally, we provide a glimpse of Euclid's ability to map the intracluster light out to larger radii than current facilities, enabling a better understanding of the cluster assembly history and mapping of the dark matter distribution. This initial dataset illustrates the diverse spectrum of legacy science that will be enabled by the Euclid survey.

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Euclid: ERO -- NISP-only sources and the search for luminous $z=6-8$ galaxies

This paper presents a search for high redshift galaxies from the Euclid Early Release Observations program "Magnifying Lens." The 1.5 deg$^2$ area covered by the twin Abell lensing cluster fields is comparable in size to the few other deep near-infrared surveys such as COSMOS, and so provides an opportunity to significantly increase known samples of rare UV-bright galaxies at $z\approx6-8$ ($M_{\rm UV}\lesssim-22$). Beyond their still uncertain role in reionisation, these UV-bright galaxies are ideal laboratories from which to study galaxy formation and constrain the bright-end of the UV luminosity function. Of the 501994 sources detected from a combined $Y_{\rm E}$, $J_{\rm E}$, and $H_{\rm E}$ NISP detection image, 168 do not have any appreciable VIS/$I_{\rm E}$ flux. These objects span a range in spectral colours, separated into two classes: 139 extremely red sources; and 29 Lyman-break galaxy candidates. Best-fit redshifts and spectral templates suggest the former is composed of both $z\gtrsim5$ dusty star-forming galaxies and $z\approx1-3$ quiescent systems. The latter is composed of more homogeneous Lyman break galaxies at $z\approx6-8$. In both cases, contamination by L- and T-type dwarfs cannot be ruled out with Euclid images alone. Additional contamination from instrumental persistence is investigated using a novel time series analysis. This work lays the foundation for future searches within the Euclid Deep Fields, where thousands more $z\gtrsim6$ Lyman break systems and extremely red sources will be identified.

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Euclid: Early Release Observations -- Programme overview and pipeline for compact- and diffuse-emission photometry

The Euclid ERO showcase Euclid's capabilities in advance of its main mission, targeting 17 astronomical objects, from galaxy clusters, nearby galaxies, globular clusters, to star-forming regions. A total of 24 hours observing time was allocated in the early months of operation, engaging the scientific community through an early public data release. We describe the development of the ERO pipeline to create visually compelling images while simultaneously meeting the scientific demands within months of launch, leveraging a pragmatic, data-driven development strategy. The pipeline's key requirements are to preserve the image quality and to provide flux calibration and photometry for compact and extended sources. The pipeline's five pillars are: removal of instrumental signatures; astrometric calibration; photometric calibration; image stacking; and the production of science-ready catalogues for both the VIS and NISP instruments. We report a PSF with a full width at half maximum of 0.16" in the optical and 0.49" in the three NIR bands. Our VIS mean absolute flux calibration is accurate to about 1%, and 10% for NISP due to a limited calibration set; both instruments have considerable colour terms. The median depth is 25.3 and 23.2 AB mag with a SNR of 10 for galaxies, and 27.1 and 24.5 AB mag at an SNR of 5 for point sources for VIS and NISP, respectively. Euclid's ability to observe diffuse emission is exceptional due to its extended PSF nearly matching a pure diffraction halo, the best ever achieved by a wide-field, high-resolution imaging telescope. Euclid offers unparalleled capabilities for exploring the LSB Universe across all scales, also opening a new observational window in the NIR. Median surface-brightness levels of 29.9 and 28.3 AB mag per square arcsec are achieved for VIS and NISP, respectively, for detecting a 10 arcsec x 10 arcsec extended feature at the 1 sigma level.

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A dusty proto-cluster surrounding the binary galaxy HerBS-70 at $z = 2.3$

We report on deep SCUBA-2 observations at 850$μ$m and NOEMA spectroscopic measurements at 2 mm of the environment surrounding the luminous, massive ($M_{*} \approx 2 \times 10^{11}$ M$_{\odot}$) Herschel-selected source HerBS-70. This source was revealed by previous NOEMA observations to be a binary system of dusty star-forming galaxies at $z= 2.3$, with the East component (HerBS-70E) hosting an Active Galactic Nucleus (AGN). The SCUBA-2 observations detected, in addition to the binary system, twenty-one sources at $> 3.5 σ$ over an area of $\sim 25$ square comoving Mpc with a sensitivity of $σ_{850} = 0.75$ mJy. The surface density of continuum sources around HerBS-70 is three times higher than for field galaxies. The NOEMA spectroscopic measurements confirm the protocluster membership of three of the nine brightest sources through their CO(4 - 3) line emission, yielding a volume density 36 times higher than for field galaxies. All five confirmed sub-mm galaxies in the HerBS-70 system have relatively short gas depletion times ($80 - 500$ Myr), indicating the onset of quenching for this protocluster core due to the depletion of gas. The dark matter halo mass of the HerBS-70 system is estimated around $5 \times{} 10^{13}$ M$_{\odot}$, with a projected current-day mass of $10^{15}$ M$_{\odot}$, similar to the local Virgo and Coma clusters. These observations support the claim that DSFGs, in particular the ones with observed multiplicity, can trace cosmic overdensities.

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Euclid Preparation XXXIII. Characterization of convolutional neural networks for the identification of galaxy-galaxy strong lensing events

Forthcoming imaging surveys will potentially increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of tens of millions of galaxies will have to be inspected to identify potential candidates. In this context, deep learning techniques are particularly suitable for the finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong lensing systems on the basis of their morphological characteristics. We train and test our models on different subsamples of a data set of forty thousand mock images, having characteristics similar to those expected in the wide survey planned with the ESA mission \Euclid, gradually including larger fractions of faint lenses. We also evaluate the importance of adding information about the colour difference between the lens and source galaxies by repeating the same training on single-band and multi-band images. Our models find samples of clear lenses with $\gtrsim 90\%$ precision and completeness, without significant differences in the performance of the three architectures. Nevertheless, when including lenses with fainter arcs in the training set, the three models' performance deteriorates with accuracy values of $\sim 0.87$ to $\sim 0.75$ depending on the model. Our analysis confirms the potential of the application of CNNs to the identification of galaxy-scale strong lenses. We suggest that specific training with separate classes of lenses might be needed for detecting the faint lenses since the addition of the colour information does not yield a significant improvement in the current analysis, with the accuracy ranging from $\sim 0.89$ to $\sim 0.78$ for the different models.

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