114 citations · 396 across the 74 of their papers we have counts for
76 papers
k-Submodular Cover Problem with a Matroid Constraint
Xinru Li, Donglei Du, Qian Liu +2
We investigate k-submodular cover problem with a matroid constraint on an n-element ground set V , which seeks k disjoint subsets of V with minimal cost, where their union is an in…
Euclid Quick Data Release (Q1) Euclid spectroscopy of quasars. 2. Physical properties from spectral fitting
Euclid Collaboration, J. Calhau, G. Calderone +312
A substantial volume of spectroscopic data has become available with the Euclid Data Release (Q1), which represents a unique opportunity to study quasars (QSOs) in the Euclid Deep…
Euclid. A two-point correlation approach to diagnosing star-related systematics in the Euclid spectroscopic survey
Euclid Collaboration, I. Risso, B. R. Granett +298
The Euclid spectroscopic survey will measure galaxy clustering with unprecedented precision, requiring stringent control of observational and instrumental systematics. Star-related…
Euclid preparation. The shape of halo profiles in CDM and non-standard cosmologies
Euclid Collaboration, L. Pizzuti, G. Y. Ferron +304
We study the shape of three-dimensional and projected dark-matter halo profiles extracted from cosmological -body simulations in CDM and non-standard cosmologies, using the \…
Euclid preparation. First investigation of the impact of cross-contamination on spectroscopic redshift measurements with pixel-level simulations
Euclid Collaboration, F. Passalacqua, S. Anselmi +299
We present a study on simulated data focused on understanding the performance of the spectroscopic redshift measurements with the Near-Infrared Spectrometer and Photometer (NISP) i…
Euclid: Galaxy SED reconstruction in the PHZ processing function: impact on the PSF and the role of medium-band filters
Euclid Collaboration, F. Tarsitano, C. Schreiber +301
Weak lensing surveys require accurate correction for the point spread function (PSF) when measuring galaxy shapes. For a diffraction-limited PSF, as arises in space-based missions,…
Euclid preparation. 3D reconstruction of the cosmic web with simulated Euclid Deep spectroscopic samples
Euclid Collaboration, K. Kraljic, C. Laigle +321
The ongoing Euclid mission aims to measure spectroscopic redshifts for approximately two million galaxies using the H line emission detected in near-infrared slitless spectrosc…
Euclid preparation. Calibrated intrinsic galaxy alignments in the Euclid Flagship simulation
Euclid Collaboration, K. Hoffmann, R. Paviot +298
Intrinsic alignments of galaxies are potentially a major contaminant of cosmological analyses of weak gravitational lensing. We construct a semi-analytic model of galaxy ellipticit…
Euclid preparation. Testing analytic models of galaxy intrinsic alignments in the Euclid Flagship simulation
Euclid Collaboration, R. Paviot, B. Joachimi +293
We model intrinsic alignments (IA) in Euclid's Flagship simulation to investigate its impact on Euclid's weak lensing signal. Our IA implementation in the Flagship simulation takes…
Euclid preparation. Galaxy 2-point correlation function modelling in redshift space
Euclid Collaboration, M. Kärcher, M. -A. Breton +309
The Euclid satellite will measure spectroscopic redshifts for tens of millions of emission-line galaxies. In the context of Stage-IV surveys, the 3-dimensional clustering of galaxi…
Euclid preparation. Galaxy power spectrum modelling in redshift space
Euclid Collaboration, B. Camacho Quevedo, M. Crocce +292
Accurate modelling of redshift-space distortions (RSD) is essential for maximizing the cosmological information extracted from large galaxy redshift surveys. In preparation for the…
Euclid preparation. Review of forecast constraints on dark energy and modified gravity
Euclid Collaboration, N. Frusciante, M. Martinelli +326
The Euclid mission has been designed to provide, as one of its main deliverables, information on the nature of the gravitational interaction, which determines the expansion of the…
Euclid Quick Data Release (Q1). From simulations to sky: Advancing machine-learning lens detection with real Euclid data
Euclid Collaboration, N. E. P. Lines, T. E. Collett +301
In the era of large-scale surveys like Euclid, machine learning has become an essential tool for identifying rare yet scientifically valuable objects, such as strong gravitational…
Euclid Quick Data Release (Q1): Euclid spectroscopy of quasars. 1. Identification and redshift determination of 3500 bright quasars
Euclid Collaboration, Y. Fu, R. Bouwens +354
The slitless spectroscopy mode of the NISP onboard Euclid has enabled efficient spectroscopy of objects within a large FoV. We present a large and homogeneous sample of bright quas…
Euclid preparation: LXXXI. The impact of nonparametric star formation histories on spatially resolved galaxy property estimation using synthetic Euclid images
Euclid Collaboration, A. Nersesian, Abdurro'uf +283
We analyzed the spatially resolved and global star formation histories (SFHs) for a sample of 25 TNG50-SKIRT Atlas galaxies to assess the feasibility of reconstructing accurate SFH…
Euclid Quick Data Release (Q1): Hunting for luminous z > 6 galaxies in the Euclid Deep Fields -- forecasts and first bright detections
Euclid Collaboration, N. Allen, P. A. Oesch +309
The evolution of the rest-frame ultraviolet luminosity function (UV LF) is a powerful probe of early star formation and stellar mass build-up. At z > 6, its bright end (MUV < -21)…
Cognitive bias in LLM reasoning compromises interpretation of clinical oncology notes
Matthew W. Kenaston, Umair Ayub, Mihir Parmar +14
Despite high performance on clinical benchmarks, large language models may reach correct conclusions through faulty reasoning, a failure mode with safety implications for oncology…
Euclid Quick Data Release (Q1): Identification of massive galaxy candidates at the end of the Epoch of Reionisation
Euclid Collaboration, R. Navarro-Carrera, K. I. Caputi +295
Probing the presence and properties of massive galaxies at high redshift is one of the most critical tests for galaxy formation models. In this work, we search for galaxies with st…
Euclid Quick Data Release (Q1). Spectroscopic unveiling of highly ionised lines at z = 2.48-3.88
Euclid Collaboration, D. Vergani, S. Quai +316
This study explores a rare population of sources in a currently uncharted region of spectroscopic redshift space in the Euclid Quick Data Release (Q1), and is intended potentially…
Euclid preparation. XCII. Controlling angular systematics in the Euclid spectroscopic galaxy sample
Euclid Collaboration, P. Monaco, M. Y. Elkhashab +298
We present the strategy used to identify and mitigate potential sources of angular systematics in the \textit{Euclid} spectroscopic galaxy survey, and we quantify their impact on g…
Euclid Quick Data Release (Q1). Searching for giant gravitational arcs in galaxy clusters with mask region-based convolutional neural networks
Euclid Collaboration, L. Bazzanini, G. Angora +306
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 e…
Euclid Quick Data Release (Q1). The average far-infrared properties of Euclid-selected star-forming galaxies
Euclid Collaboration, R. Hill, A. Abghari +302
The first Euclid Quick Data Release contains millions of galaxies with excellent optical and near-infrared (IR) coverage. To complement this dataset, we investigate the average far…
Euclid preparation: The flat-sky approximation for the clustering of Euclid's photometric galaxies
Euclid Collaboration, W. L. Matthewson, R. Durrer +277
We compare the performance of the flat-sky approximation and Limber approximation for the clustering analysis of the photometric galaxy catalogue of Euclid. We study a 6 bin config…
Euclid preparation. Cosmology Likelihood for Observables in Euclid (CLOE). 6: Impact of systematic uncertainties on the cosmological analysis
Euclid Collaboration, L. Blot, K. Tanidis +309
Extracting cosmological information from the Euclid galaxy survey will require modelling numerous systematic effects during the inference process. This implies varying a large numb…