Christopher Duncan

Abstract:

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 deg 2 . 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.

Abstract:

The Euclid satellite is an ESA mission that was launched in July 2023. Euclid is working in its regular observing mode with the target of observing an area of 14 000 deg 2 with two instruments, the Visible Camera (VIS) and the Near IR Spectrometer and Photometer (NISP) down to I E = 24.5 mag (10 σ ) in the Euclid Wide Survey. Ground-based imaging data in the ugriz bands complement the Euclid data to enable photo- z determination and VIS PSF modelling for weak lensing analysis. Euclid investigates the distance-redshift relation and the evolution of cosmic structures by measuring the shapes and redshifts of galaxies and clusters of galaxies out to z ∼ 2. Generating the multi-wavelength catalogues from Euclid and ground-based data is an essential part of the Euclid data processing system. In the framework of the Euclid Science Ground Segment (SGS), the aim of the MERge Processing Function (MER PF) pipeline is to detect objects in the Euclid imaging data, measure their properties, and merge them into a single multi-wavelength catalogue. The MER PF pipeline performs source detection on both visible (VIS) and near-infrared (NIR) images and offers four different photometric measurements: Kron total flux, aperture photometry on PSF-matched images, template fitting photometry, and Sérsic fitting photometry. Furthermore, the MER PF pipeline measures a set of ancillary quantities, spanning from morphology to quality flags, to better characterise all detected sources. In this paper, we show how the MER PF pipeline is designed, detailing its main steps, and we show that the pipeline products meet the tight requirements that Euclid aims to achieve on photometric accuracy. We also present the other measurements (e.g., morphology) that are included in the OU-MER output catalogues and we list all output products coming out of the MER PF pipeline.

Abstract:

The well-known bimodality between star-forming discs and quiescent spheroids requires the existence of two main processes: galaxy quenching, causing the strong reduction of star formation, and morphological transformation, causing the transition from disc-dominated structures to bulge-dominated ones. In this paper, we aim to understand the link between these two processes and their relation with the stellar mass of galaxies and their local environment. Taking advantage of the first data released by the Euclid Collaboration, covering more than 60 deg 2 with space-based imaging and photometry, we analyse a mass-complete sample of nearly one million galaxies in the range 0.25 < z < 1 with M * > 10 9.5 M ⊙ , using a combination of photometric and spectroscopic redshifts. We divide the sample into four sub-populations of galaxies, based on their star-formation activity (star-forming and quiescent) and morphology (disc-dominated and bulge-dominated). We then analyse the physical properties of these populations and their relative abundances in the stellar mass versus local density plane. Together with confirming the passivity-density relation and the morphology-density relation, we find that quiescent discy galaxies are more abundant in the low-mass regime of high-density environment where log 10 (1 + δ ) > 1.3. At the same time, star-forming bulge-dominated galaxies are more common in field regions with log 10 (1 + δ ) < 0.8, preferentially at high masses. Building on these results and interpreting them through comparison with simulations, we propose a scenario where the evolution of galaxies in the field significantly differs from that in higher-density environments. The morphological transformation in the majority of field galaxies takes place before the onset of quenching and is mainly driven by secular processes taking place within the main sequence, leading to the formation of star-forming bulge-dominated galaxies as intermediate-stage galaxies. Conversely, quenching of star formation precedes morphological transformation for most galaxies in higher-density environments. This causes the formation of quiescent disc-dominated galaxies before their transition into bulge-dominated ones.

Abstract:

The slitless spectroscopy mode of the Near-Infrared Spectrometer and Photometer (NISP) on board the Euclid telescope has enabled efficient spectroscopy of objects within a large field of view. Nevertheless, the relatively low spectral resolution, overlapping spectra, and contamination pose challenges to source classification and redshift determination using the NISP spectra alone. In this work, we present a large and homogeneous sample of bright quasars identified from the Euclid Quick Data Release (Q1), constructed by combining high-purity candidate selections from Gaia and WISE with the new spectroscopic capabilities of Euclid . Through visual inspection of the Euclid spectra of these quasar candidates, we identify approximately 3500 quasars and determine reliable redshifts in the range of 0 < z ≲ 4.8. Of these, 2686 are new spectroscopic identifications relative to existing public compilations. We generated the first Euclid composite spectrum of quasars covering rest-frame near-ultraviolet (NUV) to near-infrared (NIR) wavelengths without telluric lines, which will be pivotal to NIR quasar spectral analysis. We obtained an empirical spectroscopic depth of J E ≲ 21.5 and H E ≲ 21.3 at the sensitivity of the Wide Field Survey, beyond which the number of securely identified quasars declines sharply. Accordingly, the sample presented in this paper comprises spectroscopically confirmed quasars brighter than these limits. We analysed morphological parameters from the Visible Camera (VIS) using Sérsic and model-independent (CAS) metrics, and a deep-learning point spread function fraction ( f PSF ) to track nuclear dominance. The VIS morphologies show a clear redshift dependence: at low redshift ( z < 0.5), obvious host structures are common and a single Sérsic model fits about half of the sources; at intermediate redshift (0.5 < z < 2), the nuclear component dominates, with 90% of the Sérsic fits saturating at the upper index limit. In this intermediate redshift regime, f PSF is available, and we use it as a more reliable compactness measure than the single-Sérsic and CAS parameters to quantify nuclear versus host emission. We also explore the novel Euclid NIR colour space and discuss the role of these quasars in refining active galactic nucleus selection techniques for future Euclid data releases.

Abstract:

We compared the performance of the flat-sky approximation and Limber approximation for the clustering analysis of the photometric galaxy catalogue of Euclid . We studied a 6-bin configuration, representing the first data release (DR1), and a 13-bin configuration, representing the third and final data release (DR3). We find that the Limber approximation is sufficiently accurate for the analysis of the wide bins of DR1. Instead, the 13 bins of DR3 cannot be modelled accurately with the Limber approximation. Instead, the flat-sky approximation is accurate to below 5% in recovering the angular power spectra of galaxy number counts in both cases and can be used to simplify the computation of the full power spectrum in harmonic space for the data analysis of DR3.