arXiv subjects

G. Di Rosa

Publications and source records attributed to G. Di Rosa.

5 recordsLinked to original sources

arXiv2026

A new $H_0$ measurement with SNe Requiem and Encore using $\texttt{Gravity.jl}$

We present a strong-lensing (SL) analysis of the galaxy cluster MACS J0138.0-2155 (z=0.336), the first known lens cluster discovered to host two distinct multiply imaged Type Ia supernovae (SNe): SN Requiem and SN Encore. Both SNe are located in the massive, multiply imaged red galaxy MRG-M0138 at z=1.949. The projected total mass of this cluster has been investigated with several independent lens models (Suyu+26; Pierel+26), using a sample of 23 spectroscopically confirmed multiple images from 8 background sources (0.767 10%). The forthcoming reappearance of SN Requiem offers an immediate opportunity to significantly improve constraints on H0, provided that lens-model systematics are controlled. These results establish M0138 as a premier anchor for high-precision cluster-scale TDC.

astro-ph.CO↗

arXiv2026

Cosmic Duets I. High-spatial resolution spectroscopy of dual and lensed AGN with MUSE-NFM

We present the first-year results of the MUSE Large Program "Cosmic Duets", whose goal is to obtain adaptive-optics assisted MUSE observations with an angular resolution of 0.1"-0.2" in order to provide integral-field spectroscopy of sub-arcsec separation dual and lensed active galactic nucleus (AGN) candidates. These observations reveal previously unexplored properties of dual and lensed systems that are key to understanding galaxy evolution, supermassive black hole mergers, and strong-lensing modeling. Targets were efficiently selected using the Gaia multipeak (GMP) technique, which identifies pairs of point-like sources with separations below 0.8" in the Gaia catalog. MUSE spatially resolved spectroscopy provides accurate redshifts, ionization diagnostics, and identification of absorption systems along the line of sight. We report results for 30 GMP targets at z=0.5-3.5. All systems show at least 2 spatially resolved components. 19 objects are confirmed as AGN multiplets, including 6 dual AGN, 10 doubly lensed quasars, and 3 quadruply lensed systems, while the remaining 11 correspond to chance alignments with foreground stars. Among all the spectroscopically confirmed dual AGN in the literature, 27 pairs have projected separations below 7kpc in this redshift regime, and our sample accounts for 22% of the total. We studied dual and lensed AGN distributions as a function of redshift, magnitude, and projected separation while accounting for selection effects, and we find that bright systems are dominated by lensed quasars, whereas the relative fraction of dual AGN increases at fainter magnitudes. This first-year sample demonstrates the high efficiency of GMP selection combined with MUSE spectroscopy for identifying sub-arcsec dual and lensed AGN. The full program, targeting 150 systems, will enable statistical studies of dual AGN and constraints on mass distribution in lensing galaxies.

astro-ph.GA↗

arXiv2026

Euclid Quick Data Release (Q1). Searching for giant gravitational arcs in galaxy clusters with mask region-based convolutional neural networks

Strong gravitational lensing (SL) by galaxy clusters is a powerful probe of their inner mass distribution and a key test bed for cosmological models. However, the detection of SL events in wide-field surveys such as Euclid requires robust, automated methods capable of handling the immense data volume generated. In this work, we present an advanced deep learning (DL) framework based on mask region-based convolutional neural networks (Mask R-CNNs), designed to autonomously detect and segment bright, strongly-lensed arcs in Euclid's multi-band imaging of galaxy clusters. The model is trained on a realistic simulated data set of cluster-scale SL events, constructed by injecting mock background sources into Euclidised Hubble Space Telescope images of 10 massive lensing clusters, exploiting their high-precision mass models constructed with extensive spectroscopic data. The network is trained and validated on over 4500 simulated images, and tested on an independent set of 500 simulations, as well as real Euclid Quick Data Release (Q1) observations. The trained network achieves high performance in identifying gravitational arcs in the test set, with a precision and recall of 76% and 58%, respectively, processing 2'x2' images in a fraction of a second. When applied to a sample of visually confirmed Euclid Q1 cluster-scale lenses, our model recovers 66% of gravitational arcs above the area threshold used during training. While the model shows promising results, limitations include the production of some false positives and challenges in detecting smaller, fainter arcs. Our results demonstrate the potential of advanced DL computer vision techniques for efficient and scalable arc detection, enabling the automated analysis of SL systems in current and future wide-field surveys. The code, ARTEMIDE, is open source and will be available at github.com/LBasz/ARTEMIDE.

astro-ph.CO↗

arXiv2025

A new quasar strongly-lensed candidate by the galaxy cluster WHJ0400-27 with a $18''$ image-separation

Time-delay cosmography (TDC) using multiply-lensed quasars (QSOs) by galaxies has recently emerged as an independent and competitive tool to measure the value of the Hubble constant. Lens galaxy clusters hosting multiply-imaged QSOs, when coupled with an accurate and precise knowledge of their total mass distribution, are equally powerful cosmological probes. However, less than ten such systems have been identified to date. Our study aims to expand the limited sample of cluster-lensed QSO systems by identifying new candidates within rich galaxy clusters. Starting from a sample of ~$10^5$ galaxy cluster candidates (Wen & Han, 2022), built from Dark Energy Survey and Wide-field Infrared Survey Explorer imaging data, and a highly-pure catalogue of over one million QSOs, based on Gaia DR3 data, we cross-correlate them to identify candidate lensed QSOs near the core of massive galaxy clusters. Our search yielded 3 lensed double candidates over an area of ~$5000$ sq. degree. In this work, we focus on the best candidate consisting of a double QSO with Gaia-based redshift of 1.35, projected behind a moderately rich cluster (WHJ0400-27) at $z_{phot}=0.65$. Based on a first spectroscopic follow-up study, we confirm the two QSOs at $z=1.345$, with indistinguishable spectra, and a brightest cluster galaxy at $z=0.626$. These observations seem to support the strong lensing nature of this system, although some tension emerges when the cluster mass from a preliminary lens model is compared with that from other mass proxies. We also discuss the possibility that such system is a rare physical association of two distinct QSOs with a projected physical distance of ~$150$ kpc. If further spectroscopic observations confirm its lensing nature, such a rare lens system would exhibit one of the largest image separations observed to date ($Δ\vartheta=17.8''$), opening interesting TDC applications.

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↗