Search for: All records

ABSTRACT With the launch of eROSITA (extended Roentgen Survey with an Imaging Telescope Array), successfully occurred on 2019 July 13, we are facing the challenge of computing reliable photometric redshifts for 3 million of active galactic nuclei (AGNs) over the entire sky, having available only patchy and inhomogeneous ancillary data. While we have a good understanding of the photo-z quality obtainable for AGN using spectral energy distribution (SED)-fitting technique, we tested the capability of machine learning (ML), usually reliable in computing photo-z for QSO in wide and shallow areas with rich spectroscopic samples. Using MLPQNA as example of ML, we computed photo-z for the X-ray-selected sources in Stripe 82X, using the publicly available photometric and spectroscopic catalogues. Stripe 82X is at least as deep as eROSITA will be and wide enough to include also rare and bright AGNs. In addition, the availability of ancillary data mimics what can be available in the whole sky. We found that when optical, and near- and mid-infrared data are available, ML and SED fitting perform comparably well in terms of overall accuracy, realistic redshift probability density functions, and fraction of outliers, although they are not the same for the two methods. The results could further improve if the photometry available is accurate and including morphological information. Assuming that we can gather sufficient spectroscopy to build a representative training sample, with the current photometry coverage we can obtain reliable photo-z for a large fraction of sources in the Southern hemisphere well before the spectroscopic follow-up, thus timely enabling the eROSITA science return. The photo-z catalogue is released here. 

This paper presents a search for high redshift galaxies from theEuclidEarly Release Observations program ‘Magnifying Lens.’ The 1.5 deg²area 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 atz≈ 6–8 (M_UV≲ −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 501 994 sources detected from a combinedY_E,J_E, andH_ENISP detection image, 168 do not have any appreciable VIS/I_Eflux. 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 bothz≳ 5 dusty star-forming galaxies andz≈ 1–3 quiescent systems. The latter is composed of more homogeneous Lyman-break galaxies atz≈ 6–8. In both cases, contamination by L- and T-type dwarfs cannot be ruled out withEuclidimages 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 morez≳ 6 Lyman-break systems and extremely red sources will be identified. 

Dark matter may induce an event in an Earth-based detector, and its event rate is predicted to show an annual modulation as a result of the Earth’s orbital motion around the Sun. We searched for this modulation signature using the ionization signal of the DarkSide-50 liquid argon time projection chamber. No significant signature compatible with dark matter is observed in the electron recoil equivalent energy range above $40{\mathrm{eV}}_{\mathrm{ee}}$, the lowest threshold ever achieved in such a search. Published by the American Physical Society2024 

Abstract The stability of a dark matter detector on the timescale of a few years is a key requirement due to the large exposure needed to achieve a competitive sensitivity. It is especially crucial to enable the detector to potentially detect any annual event rate modulation, an expected dark matter signature. In this work, we present the performance history of the DarkSide-50 dual-phase argon time projection chamber over its almost three-year low-radioactivity argon run. In particular, we focus on the electroluminescence signal that enables sensitivity to sub-keV energy depositions. The stability of the electroluminescence yield is found to be better than 0.5%. Finally, we show the temporal evolution of the observed event rate around the sub-keV region being consistent to the background prediction. 

We report the discovery of a complete Einstein ring around the elliptical galaxy NGC 6505, atz = 0.042. This is the first strong gravitational lens discovered inEuclidand 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_E = 18.1 lensed,I_E = 21.3 unlensed), and the completeness of the ring make this an exceptionally rare strong lens, unidentified until its observation byEuclid. We present deep imaging data of the lens from theEuclidVisible Camera (VIS) and Near-Infrared Spectrometer and Photometer (NISP) instruments, as well as resolved spectroscopy from theKeckCosmic Web Imager (KCWI). TheEuclidimaging 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 ofz = 0.406. Using data from the Dark Energy Spectroscopic Instrument (DESI) we measure a velocity dispersion for the lens galaxy ofσ_⋆ = 303 ± 15 km s⁻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, corresponding to 2.1 kpc at the redshift of the lens. This is small compared to the effective radius of the galaxy,R_eff ∼ 12.″3. Combining the strong lensing measurements with analysis of the spectroscopic data we estimate a dark matter fraction inside the Einstein radius off_DM = (11.1_−3.5^+5.4)% and a stellar initial mass-function (IMF) mismatch parameter ofα_IMF = 1.26_−0.08^+0.05, indicating a heavier-than-Chabrier IMF in the centre of the galaxy. 

The Cosmic Dawn Survey (DAWN survey) provides multiwavelength (UV/optical to mid-IR) data across the combined 59 deg²of the Euclid Deep and Auxiliary fields (EDFs and EAFs). In this work, the first public data release from the DAWN survey is presented. The catalogues made available herein consist of a subset of the full DAWN survey that includes two EDFs: EDF North (EDF-N) and EDF Fornax (EDF-F). Each field has been covered by the ongoing Hawaii Twenty Square Degree Survey (H20), which includes imaging from the CFHT MegaCam in theufilter and from the Subaru Hyper Suprime-Cam (HSC) in thegrizfilters. Each field has been further covered bySpitzer/IRAC 3.6–4.5µm imaging spanning 10 deg²and reaching ~25 mag AB (5σ). All present H20 imaging and all publicly available imaging from the aforementioned facilities were combined with the deepSpitzer/IRAC data to create source catalogues spanning a total area of 16.87 deg²in EDF-N and 2.85 deg²in EDF-F for this first release. These catalogues are referred to as the ‘pre-launch’ (PL), asEucliddata is not yet public for these fields and therefore it is not included. Photometry was measured from these multiwavelength data usingThe Farmer, a novel and well validated model-based photometry code. Photometric redshifts and stellar masses were computed using two independent codes for modelling spectral energy distributions:EAZYandLePhare. Photometric redshifts show good agreement with spectroscopic redshifts (σ_NMAD~ 0.5,η <8% ati< 25). Number counts, photometric redshifts and stellar masses were further validated in comparison to the COSMOS2020 catalogue. The DAWN survey PL catalogues are designed to be of immediate use in these two EDFs and will be continuously updated and made available as both new ground-based data and spaced-based data fromEuclidare acquired and made public. Future data releases will provide catalogues of all EDFs and EAFs and includeEucliddata. 

Euclidwill provide deep near-infrared (NIR) imaging to ∼26.5 AB magnitude over ∼59 deg²in its deep and auxiliary fields. The Cosmic DAWN survey combines dedicated and archival UV–NIR observations to provide matched depth multiwavelength imaging of theEucliddeep and auxiliary fields. The DAWN survey will provide consistently measuredEuclidNIR-selected photometric catalogues, accurate photometric redshifts, and measurements of galaxy properties to a redshift ofz ∼ 10. The DAWN catalogues includeSpitzerIRAC data that are critical for stellar mass measurements atz ≳ 2.5 and high-zscience. These catalogues complement the standardEuclidcatalogues, which will not includeSpitzerIRAC data. In this paper, we present an overview of the survey, including the footprints of the survey fields, the existing and planned observations, and the primary science goals for the combined data set. 

Abstract We present a novel approach for the search of dark matter in the DarkSide-50 experiment, relying on Bayesian Networks. This method incorporates the detector response model into the likelihood function, explicitly maintaining the connection with the quantity of interest. No assumptions about the linearity of the problem or the shape of the probability distribution functions are required, and there is no need to morph signal and background spectra as a function of nuisance parameters. By expressing the problem in terms of Bayesian Networks, we have developed an inference algorithm based on a Markov Chain Monte Carlo to calculate the posterior probability. A clever description of the detector response model in terms of parametric matrices allows us to study the impact of systematic variations of any parameter on the final results. Our approach not only provides the desired information on the parameter of interest, but also potential constraints on the response model. Our results are consistent with recent published analyses and further refine the parameters of the detector response model.