8 research outputs found

    HOLISMOKES XIII: Strong-lens candidates at all mass scales and their environments from the Hyper-Suprime Cam and deep learning

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    International audienceWe have performed a systematic search for galaxy-scale strong lenses using Hyper Suprime-Cam imaging data, focusing on lenses in overdense environments. To identify these lens candidates, we exploit our neural network from HOLISMOKES VI, which is trained on realistic gri mock-images as positive examples, and real images as negative examples. Compared to our previous work, we lower the i-Kron radius limit to >0.5". This results in an increase by around 73 million sources to more than 135 million images. During our visual multi-stage grading of the network candidates, we now inspect simultaneously larger stamps (80"x80") to identify large, extended arcs cropped in the 10"x10" cutouts, and classify additionally their overall environment. Here we also reinspect our previous lens candidates and classify their environment. Using these 546 visually identified lens candidates, we further define various criteria by exploiting extensive and complementary photometric redshift catalogs, to select the candidates in overdensities. In total, we identified 24 grade-A and 138 grade-B candidates with either spatially-resolved multiple images or extended, distorted arcs in the new sample. Furthermore, with our different techniques, we identify in total 237/546 lens candidates in a cluster-like or overdense environment, containing only 49 group- or cluster-scale re-discoveries. These results demonstrate the feasibility of downloading and applying network classifiers to hundreds of million cutouts, necessary in the upcoming era of big data from deep, wide-field imaging surveys like Euclid and the Rubin Observatory Legacy Survey of Space and Time, while leading to a sample size that can be inspected by humans. These networks, with false-positive rates of ~0.01%, are very powerful tools to identify such rare galaxy-scale strong lensing systems, while also aiding in the discovery of new strong lensing clusters

    HOLISMOKES XIII: Strong-lens candidates at all mass scales and their environments from the Hyper-Suprime Cam and deep learning

    No full text
    International audienceWe have performed a systematic search for galaxy-scale strong lenses using Hyper Suprime-Cam imaging data, focusing on lenses in overdense environments. To identify these lens candidates, we exploit our neural network from HOLISMOKES VI, which is trained on realistic gri mock-images as positive examples, and real images as negative examples. Compared to our previous work, we lower the i-Kron radius limit to >0.5". This results in an increase by around 73 million sources to more than 135 million images. During our visual multi-stage grading of the network candidates, we now inspect simultaneously larger stamps (80"x80") to identify large, extended arcs cropped in the 10"x10" cutouts, and classify additionally their overall environment. Here we also reinspect our previous lens candidates and classify their environment. Using these 546 visually identified lens candidates, we further define various criteria by exploiting extensive and complementary photometric redshift catalogs, to select the candidates in overdensities. In total, we identified 24 grade-A and 138 grade-B candidates with either spatially-resolved multiple images or extended, distorted arcs in the new sample. Furthermore, with our different techniques, we identify in total 237/546 lens candidates in a cluster-like or overdense environment, containing only 49 group- or cluster-scale re-discoveries. These results demonstrate the feasibility of downloading and applying network classifiers to hundreds of million cutouts, necessary in the upcoming era of big data from deep, wide-field imaging surveys like Euclid and the Rubin Observatory Legacy Survey of Space and Time, while leading to a sample size that can be inspected by humans. These networks, with false-positive rates of ~0.01%, are very powerful tools to identify such rare galaxy-scale strong lensing systems, while also aiding in the discovery of new strong lensing clusters

    Tracing the rise of supermassive black holes A panchromatic search for faint, unobscured quasars at z & 6 with COSMOS-Web and other surveys

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    We report the identification of 64 new candidates of compact galaxies, potentially hosting faint quasars with bolometric luminosities of Lbol = 1043–1046 erg s−1, residing in the reionization epoch within the redshift range of 6 . z . 8. These candidates were selected by harnessing the rich multiband datasets provided by the emerging JWST-driven extragalactic surveys, focusing on COSMOS-Web, as well as JADES, UNCOVER, CEERS, and PRIMER. Our search strategy includes two stages: applying stringent photometric cuts to catalog-level data and detailed spectral energy distribution fitting. These techniques effectively isolate the quasar candidates while mitigating contamination from low-redshift interlopers, such as brown dwarfs and nearby galaxies. The selected candidates indicate physical traits compatible with low-luminosity active galactic nuclei, likely hosting ≈105–107 M supermassive black holes (SMBHs) living in galaxies with stellar masses of ≈108–1010 M . The SMBHs selected in this study, on average, exhibit an elevated mass compared to their hosts, with the mass ratio distribution slightly higher than those of galaxies in the local Universe. As with other high-z studies, this is at least in part due to the selection method for these quasars. An extensive Monte Carlo analysis provides compelling evidence that heavy black hole seeds from the direct collapse scenario appear to be the preferred pathway to mature this specific subset of SMBHs by z ≈ 7. Notably, most of the selected candidates might have emerged from seeds with masses of ∌105 M , assuming a thin disk accretion with an average Eddington ratio of fEdd = 0.6±0.3 and a radiative efficiency of Δ = 0.2±0.1. This work underscores the significance of further spectroscopic observations, as the quasar candidates presented here offer exceptional opportunities to delve into the nature of the earliest galaxies and SMBHs that formed during cosmic infancy.</p

    Uncovering a Massive z∌7.7 Galaxy Hosting a Heavily Obscured Radio-loud Active Galactic Nucleus Candidate in COSMOS-Web

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    In this Letter, we report the discovery of the highest redshift, heavily obscured, radio-loud (RL) active galactic nucleus (AGN) candidate selected using JWST NIRCam/MIRI, mid-IR, submillimeter, and radio imaging in the COSMOS-Web field. Using multifrequency radio observations and mid-IR photometry, we identify a powerful, RL, growing supermassive black hole with significant spectral steepening of the radio spectral energy distribution (f1.28 GHz ∌ 2 mJy, q24 ÎŒm = −1.1, α1.28−3 GHz = − 1.2, Δα = − 0.4). In conjunction with ALMA, deep ground-based observations, ancillary space-based data, and the unprecedented resolution and sensitivity of JWST, we find no evidence of AGN contribution to the UV/optical/near-infrared (NIR) data and thus infer heavy amounts of obscuration (NH &gt; 1023 cm−2). Using the wealth of deep UV to submillimeter photometric data, we report a singular solution photo-z of zphot = 7.7-+0.30.4 and estimate an extremely massive host galaxy (log M* = 11.92 0.5M) hosting a powerful, growing supermassive black hole (LBol = 4−12x × 1046 erg s−1). This source represents the farthest known obscured RL AGN candidate, and its level of obscuration aligns with the most representative but observationally scarce population of AGN at these epochs.</p

    Uncovering a Massive z 7.7 Galaxy Hosting a Heavily Obscured Radio-loud Active Galactic Nucleus Candidate in COSMOS-Web

    No full text
    International audienceIn this Letter, we report the discovery of the highest redshift, heavily obscured, radio-loud (RL) active galactic nucleus (AGN) candidate selected using JWST NIRCam/MIRI, mid-IR, submillimeter, and radio imaging in the COSMOS-Web field. Using multifrequency radio observations and mid-IR photometry, we identify a powerful, RL, growing supermassive black hole with significant spectral steepening of the radio spectral energy distribution (f 1.28 GHz ~ 2 mJy, q 24 ÎŒm = -1.1, α 1.28-3 GHz = - 1.2, Δα = - 0.4). In conjunction with ALMA, deep ground-based observations, ancillary space-based data, and the unprecedented resolution and sensitivity of JWST, we find no evidence of AGN contribution to the UV/optical/near-infrared (NIR) data and thus infer heavy amounts of obscuration (N H > 1023 cm-2). Using the wealth of deep UV to submillimeter photometric data, we report a singular solution photo-z of z phot = 7.7−0.3+0.4{7.7}_{-0.3}^{+0.4} and estimate an extremely massive host galaxy (logM⋆=11.92±0.5M⊙)(\mathrm{log}{M}_{\star }=11.92\pm 0.5{M}_{\odot}) hosting a powerful, growing supermassive black hole (L Bol = 4-12x × 1046 erg s-1). This source represents the farthest known obscured RL AGN candidate, and its level of obscuration aligns with the most representative but observationally scarce population of AGN at these epochs
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