arXiv subjects

P. Hudelot

Publications and source records attributed to P. Hudelot.

At least 55 records · Page 3Linked to original sources

arXiv2025

Euclid Quick Data Release (Q1). Photometric redshifts and physical properties of galaxies through the PHZ processing function

The ESA Euclid mission will measure the photometric redshifts of billions of galaxies in order to provide an accurate 3D view of the Universe at optical and near-infrared wavelengths. Photometric redshifts are determined by the PHZ processing function on the basis of the multi-wavelength photometry of Euclid and ground-based observations. In this paper, we describe the PHZ processing used for the Euclid Quick Data Release, the output products, and their validation. The PHZ pipeline is responsible for the following main tasks: source classification into star, galaxy, and QSO classes based on photometric colours; determination of photometric redshifts and of physical properties of galaxies. The classification is able to provide a star sample with a high level of purity, a highly complete galaxy sample, and reliable probabilities of belonging to those classes. The identification of QSOs is more problematic: photometric information seems to be insufficient to accurately separate QSOs from galaxies. The performance of the pipeline in the determination of photometric redshifts has been tested using the COSMOS2020 catalogue and a large sample of spectroscopic redshifts. The results are in line with expectations: the precision of the estimates are compatible with Euclid requirements, while, as expected, a bias correction is needed to achieve the accuracy level required for the cosmological probes. Finally, the pipeline provides reliable estimates of the physical properties of galaxies, in good agreement with findings from the COSMOS2020 catalogue, except for an unrealistically large fraction of very young galaxies with very high specific star-formation rates. The application of appropriate priors is, however, sufficient to obtain reliable physical properties for those problematic objects. We present several areas for improvement for future Euclid data releases.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). First Euclid statistical study of the active galactic nuclei contribution fraction

Active galactic nuclei (AGN) play a key role in galaxy evolution but are challenging to identify due to their varied observational signatures. Furthermore, understanding their impact requires quantifying their strength relative to their host galaxies. We developed a deep learning (DL) model for identifying AGN in imaging data by deriving the contribution of the central point source. Trained on Euclidised mock galaxy images with injected AGN levels, in the form of varying contributions of the point-spread function (PSF), our model can precisely and accurately recover the injected AGN contribution fraction $f_{\rm PSF}$, with a mean difference between the predicted and true $f_{\rm PSF}$ of $-0.0078$ and an overall root mean square error (RMSE) of 0.051. This method moves beyond binary AGN classification, enabling precise AGN contribution measurements. Applying our model to a stellar-mass-limited sample ($M_{\ast} \ge 10^{9.8} M_{\odot}$, $0.5 \le z \le 2.0$) from the first \Euclid quick data release (Q1), we identify $48,840 \pm 78$ AGN over 63.1 deg$^2$ ($7.8\pm0.1$%) using a threshold of $f_{\rm PSF} > 0.2$. We compare our DL-selected AGN with those identified in X-ray, mid-infrared (MIR), and optical spectroscopy and investigate their overlapping fractions depending on different thresholds on the PSF contribution. We find that the overlap increases with increasing X-ray or bolometric AGN luminosity. The AGN luminosity in the $I_{\rm E}$ filter correlates with host galaxy stellar mass, suggesting faster supermassive black hole (SMBH) growth in more massive galaxies. Moreover, the mean relative contribution of the AGN is higher in quiescent galaxies than in star-forming ones. Starburst galaxies and the most massive galaxies (across the star-formation main sequence) tend to host the most luminous AGN, indicating concomitant assembly of the SMBH and the host galaxy.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1) First study of red quasars selection

Red quasars constitute an important but elusive phase in the evolution of supermassive black holes, where dust obscuration can significantly alter their observed properties. They have broad emission lines, like other quasars, but their optical continuum emission is significantly reddened, which is why they were traditionally identified based on near- and mid-infrared selection criteria. This work showcases the capability of the \Euclid space telescope to find a large sample of red quasars, using \Euclid near infrared (NIR) photometry. We first conduct a forecast analysis, comparing a synthetic catalogue of red QSOs with COSMOS2020. Using template fitting, we reconstruct \Euclid-like photometry for the COSMOS sources and identify a sample of candidates in a multidimensional colour-colour space achieving $98\%$ completeness for mock red QSOs with $30\%$ contaminants. To refine our selection function, we implement a probabilistic Random Forest classifier, and use UMAP visualisation to disentangle non-linear features in colour-space, reaching $98\%$ completeness and $88\%$ purity. A preliminary analysis of the candidates in the \Euclid Deep Field Fornax (EDF-F) shows that, compared to VISTA+DECAm-based colour selection criteria, \Euclid's superior depth, resolution and optical-to-NIR coverage improves the identification of the reddest, most obscured sources. Notably, the \Euclid exquisite resolution in the $I_E$ filter unveils the presence of a candidate dual quasar system, highlighting the potential for this mission to contribute to future studies on the population of dual AGN. The resulting catalogue of candidates, including more the 150 000 sources, provides a first census of red quasars in \Euclid Q1 and sets the groundwork for future studies in the Euclid Wide Survey (EWS), including spectral follow-up analyses and host morphology characterisation.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). An investigation of optically faint, red objects in the Euclid Deep Fields

Our understanding of cosmic star-formation at $z>3$ used to largely rely on rest-frame UV observations. However, these observations overlook dusty and massive sources, resulting in an incomplete census of early star-forming galaxies. Recently, infrared data from Spitzer and the James Webb Space Telescope (JWST) have revealed a hidden population at $z\sim$3-6 with extreme red colours. Taking advantage of the overlap between imaging in the Euclid Deep Fields (EDFs), covering $\sim$ 60 deg$^2$, and ancillary Spitzer observations, we identified 27000 extremely red objects with $H_E-{\rm IRAC}2>2.25$ (dubbed HIEROs) down to a $10σ$ completeness magnitude limit of IRAC2 $=$ 22.5 AB. After a visual inspection to discard artefacts and objects with troubling photometry, we ended up with a final sample of 3900 candidates. We retrieved the physical parameter estimates for these objects from the SED-fitting tool CIGALE. Our results confirm that HIERO galaxies may populate the high-mass end of the stellar mass function at $z>3$, with some reaching extreme stellar masses ($M_*>10^{11}M_\odot$) and exhibiting high dust attenuation ($A_V>3$). However, we consider stellar mass estimates unreliable for $z>3.5$, favouring a lower-z solution. The challenges faced by SED-fitting tools in characterising these objects highlight the need for further studies, incorporating shorter-wavelength and spectroscopic data. Euclid spectra will help resolve degeneracies and better constrain the physical properties of the brightest galaxies. Given the extreme nature of this population, characterising these sources is crucial for understanding galaxy evolution. This work demonstrates Euclid's potential to provide statistical samples of rare, massive, dust-obscured galaxies at $z>3$, which will be prime targets for JWST, ALMA, and ELT.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1). Galaxy shapes and alignments in the cosmic web

Galaxy morphologies and shape orientations are expected to correlate with their large-scale environment, since they grow by accreting matter from the cosmic web and are subject to interactions with other galaxies. Cosmic filaments are extracted in projection from the Euclid Quick Data Release 1 (covering 63.1 $\mathrm{deg}^2$) at $0.5 10^{10} M_\odot$) in the projected cosmic web is analysed as a function of morphology measured from VIS data. Specifically, the 2D alignment of galaxy shapes with large-scale filaments is quantified as a function of Sérsic indices and masses. We find the known trend that more massive galaxies are closer to filament spines. At fixed stellar masses, morphologies correlate both with densities and distances to large-scale filaments. In addition, the large volume of this data set allows us to detect a signal indicating that there is a preferential alignment of the major axis of massive early-type galaxies along projected cosmic filaments. Overall, these results demonstrate our capabilities to carry out detailed studies of galaxy environments with Euclid, which will be extended to higher redshift and lower stellar masses with the future Euclid Deep Survey.

astro-ph.GA↗

arXiv2025

Euclid: Quick Data Release (Q1) -- Photometric studies of known transients

We report on serendipitous Euclid observations of previously known transients, using the Euclid Q1 data release. By cross-matching with the Transient Name Server (TNS) we identify 164 transients that coincide with the data release. Although the Euclid Q1 release only includes single-epoch data, we are able to make Euclid photometric measurements at the location of 161 of these transients. Euclid obtained deep photometric measurements or upper limits of these transients in the $I_E$, $Y_E$, $J_E$, and $H_E$ bands at various phases of the transient light-curves, including before, during, and after the observations of ground-based transient surveys. Approximately 70\% of known transients reported in the six months before the Euclid observation date and with discovery magnitude brighter than 24 were detected in Euclid $\IE$ images. Our observations include one of the earliest near-infrared detections of a Type~Ia supernova (SN 2024pvw) 15 days prior to its peak brightness, and the late-phase (435.9 days post peak) observations of the enigmatic core-collapse SN 2023aew. Euclid deep photometry provides valuable information on the nature of these transients such as their progenitor systems and power sources, with late time observations being a uniquely powerful contribution. In addition, Euclid is able to detect the host galaxies of some transients that were previously classed as hostless. The Q1 data demonstrate the power of the Euclid data even with only single-epoch observations available, as will be the case for much larger areas of sky in the Euclid Wide Survey.

astro-ph.SR↗

arXiv2025

Euclid: Quick Data Release (Q1) -- A census of dwarf galaxies across a range of distances and environments

The Euclid Q1 fields were selected for calibration purposes in cosmology and are therefore relatively devoid of nearby galaxies. However, this is precisely what makes them interesting fields in which to search for dwarf galaxies in local density environments. We take advantage of the unprecedented depth, spatial resolution, and field of view of the Euclid Quick Release (Q1) to build a census of dwarf galaxies in these regions. We have identified dwarfs in a representative sample of 25 contiguous tiles in the Euclid Deep Field North (EDF-N), covering an area of 14.25 sq. deg. The dwarf candidates were identified using a semi-automatic detection method, based on properties measured by the Euclid pipeline and listed in the MER catalogue. A selection cut in surface brightness and magnitude was used to produce an initial dwarf candidate catalogue, followed by a cut in morphology and colour. This catalogue was visually classified to produce a final sample of dwarf candidates, including their morphology, number of nuclei, globular cluster (GC) richness, and presence of a blue compact centre. We identified 2674 dwarf candidates, corresponding to 188 dwarfs per sq. deg. The visual classification of the dwarfs reveals a slightly uneven morphological mix of 58% ellipticals and 42% irregulars, with very few potentially GC-rich (1.0%) and nucleated (4.0%) candidates but a noticeable fraction (6.9%) of dwarfs with blue compact centres. The distance distribution of 388 (15%) of the dwarfs with spectroscopic redshifts peaks at about 400 Mpc. Their stellar mass distribution confirms that our selection effectively identifies dwarfs while minimising contamination. The most prominent dwarf overdensities are dominated by dEs, while dIs are more evenly distributed. This work highlights Euclid's remarkable ability to detect and characterise dwarf galaxies across diverse masses, distances, and environments.

astro-ph.GA↗

arXiv2025

Euclid Quick Data Release (Q1): From spectrograms to spectra: the SIR spectroscopic Processing Function

The Euclid space mission aims to investigate the nature of dark energy and dark matter by mapping the large-scale structure of the Universe. A key component of Euclid's observational strategy is slitless spectroscopy, conducted using the Near Infrared Spectrometer and Photometer (NISP). This technique enables the acquisition of large-scale spectroscopic data without the need for targeted apertures, allowing precise redshift measurements for millions of galaxies. These data are essential for Euclid's core science objectives, including the study of cosmic acceleration and the evolution of galaxy clustering, as well as enabling many non-cosmological investigations. This study presents the SIR processing function (PF), which is responsible for processing slitless spectroscopic data. The objective is to generate science-grade fully-calibrated one-dimensional spectra, ensuring high-quality spectroscopic data. The processing function relies on a source catalogue generated from photometric data, effectively corrects detector effects, subtracts cross-contaminations, minimizes self-contamination, calibrates wavelength and flux, and produces reliable spectra for later scientific use. The first Quick Data Release (Q1) of Euclid's spectroscopic data provides approximately three million validated spectra for sources observed in the red-grism mode from a selected portion of the Euclid Wide Survey. We find that wavelength accuracy and measured resolving power are within requirements, thanks to the excellent optical quality of the instrument. The SIR PF represents a significant step in processing slitless spectroscopic data for the Euclid mission. As the survey progresses, continued refinements and additional features will enhance its capabilities, supporting high-precision cosmological and astrophysical measurements.

astro-ph.IM↗

arXiv2025

Euclid: Early Release Observations -- The Intracluster Light of Abell 2390

Intracluster light (ICL) provides a record of the dynamical interactions undergone by clusters, giving clues on cluster formation and evolution. Here, we analyse the properties of ICL in the massive cluster Abell 2390 at redshift z=0.228. Our analysis is based on the deep images obtained by the Euclid mission as part of the Early Release Observations in the near-infrared (Y, J, H bands), using the NISP instrument in a 0.75 deg$^2$ field. We subtracted a point--spread function (PSF) model and removed the Galactic cirrus contribution in each band after modelling it with the DAWIS software. We then applied three methods to detect, characterise, and model the ICL and the brightest cluster galaxy (BCG): the CICLE 2D multi-galaxy fitting; the DAWIS wavelet-based multiscale software; and a mask-based 1D profile fitting. We detect ICL out to 600 kpc. The ICL fractions derived by our three methods range between 18% and 36% (average of 24%), while the BCG+ICL fractions are between 21% and 41% (average of 29%), depending on the band and method. A galaxy density map based on 219 selected cluster members shows a strong cluster substructure to the south-east and a smaller feature to the north-west. Based on colours, the ICL (out to about 400 kpc) seems to be built by the accretion of small systems (M ~ $10^{9.5}$ solar mass), or from stars coming from the outskirts of Milky Way-type galaxies (M ~ $10^{10}$ solar mass). Though Abell 2390 does not seem to be undergoing a merger, it is not yet fully relaxed, since it has accreted two groups that have not fully merged with the cluster core. We estimate that the contributions to the inner 300 kpc of the ICL of the north-west and south-east subgroups are 21% and 9% respectively.

astro-ph.GA↗

arXiv2025

Euclid preparation LX. The use of HST images as input for weak-lensing image simulations

Data from the Euclid space telescope will enable cosmic shear measurements with very small statistical errors, requiring corresponding systematic error control level. A common approach to correct for shear biases involves calibrating shape measurement methods using image simulations with known input shear. Given their high resolution, Hubble Space Telescope (HST) galaxies can, in principle, be utilised to emulate Euclid observations. In this work, we employ a GalSim-based testing environment to investigate whether uncertainties in the HST point spread function (PSF) model or in data processing techniques introduce significant biases in weak-lensing (WL) shear calibration. We used single Sérsic galaxy models to simulate both HST and Euclid observations. We then `Euclidised' our HST simulations and compared the results with the directly simulated Euclid-like images. For this comparison, we utilised a moment-based shape measurement algorithm and galaxy model fits. Through the Euclidisation procedure, we effectively reduced the residual multiplicative biases in shear measurements to sub-percent levels. This achievement was made possible by employing either the native pixel scales of the instruments, utilising the Lanczos15 interpolation kernel, correcting for noise correlations, and ensuring consistent galaxy signal-to-noise ratios between simulation branches. However, the Euclidisation procedure requires further analysis on the impact of the correlated noise, to estimate calibration bias. Additionally, we conducted an in-depth analysis of the accuracy of TinyTim HST PSF models using star fields observed in the F606W and F814W filters. We observe that F606W images exhibit a broader scatter in the recovered best-fit focus, compared to those in the F814W filter.

astro-ph.CO↗

arXiv2025

Euclid: Detecting Solar System objects in Euclid images and classifying them using Kohonen self-organising maps

The ESA Euclid mission will survey more than 14,000 deg$^2$ of the sky in visible and near-infrared wavelengths, mapping the extra-galactic sky to constrain our cosmological model of the Universe. Although the survey focusses on regions further than 15 deg from the ecliptic, it should allow for the detection of more than about $10^5$ Solar System objects (SSOs). After simulating the expected signal from SSOs in Euclid images acquired with the visible camera (VIS), we describe an automated pipeline developed to detect moving objects with an apparent velocity in the range of 0.1-10 arcsec/h, typically corresponding to sources in the outer Solar System (from Centaurs to Kuiper-belt objects). In particular, the proposed detection scheme is based on Sourcextractor software and on applying a new algorithm capable of associating moving objects amongst different catalogues. After applying a suite of filters to improve the detection quality, we study the expected purity and completeness of the SSO detections. We also show how a Kohonen self-organising neural network can be successfully trained (in an unsupervised fashion) to classify stars, galaxies, and SSOs. By implementing an early-stopping method in the training scheme, we show that the network can be used in a predictive way, allowing one to assign the probability of each detected object being a member of each considered class.

astro-ph.IM↗

arXiv2024

Euclid preparation. LVIII. Detecting globular clusters in the Euclid survey

Extragalactic globular clusters (EGCs) are an abundant and powerful tracer of galaxy dynamics and formation, and their own formation and evolution is also a matter of extensive debate. The compact nature of globular clusters means that they are hard to spatially resolve and thus study outside the Local Group. In this work we have examined how well EGCs will be detectable in images from the Euclid telescope, using both simulated pre-launch images and the first early-release observations of the Fornax galaxy cluster. The Euclid Wide Survey will provide high-spatial resolution VIS imaging in the broad IE band as well as near-infrared photometry (YE, JE, and HE). We estimate that the galaxies within 100 Mpc in the footprint of the Euclid survey host around 830 000 EGCs of which about 350 000 are within the survey's detection limits. For about half of these EGCs, three infrared colours will be available as well. For any galaxy within 50Mpc the brighter half of its GC luminosity function will be detectable by the Euclid Wide Survey. The detectability of EGCs is mainly driven by the residual surface brightness of their host galaxy. We find that an automated machine-learning EGC-classification method based on real Euclid data of the Fornax galaxy cluster provides an efficient method to generate high purity and high completeness GC candidate catalogues. We confirm that EGCs are spatially resolved compared to pure point sources in VIS images of Fornax. Our analysis of both simulated and first on-sky data show that Euclid will increase the number of GCs accessible with high-resolution imaging substantially compared to previous surveys, and will permit the study of GCs in the outskirts of their hosts. Euclid is unique in enabling systematic studies of EGCs in a spatially unbiased and homogeneous manner and is primed to improve our understanding of many understudied aspects of GC astrophysics.

astro-ph.GA↗

arXiv2024

Euclid preparation: Determining the weak lensing mass accuracy and precision for galaxy clusters

We investigate the level of accuracy and precision of cluster weak-lensing (WL) masses measured with the \Euclid data processing pipeline. We use the DEMNUni-Cov $N$-body simulations to assess how well the WL mass probes the true halo mass, and, then, how well WL masses can be recovered in the presence of measurement uncertainties. We consider different halo mass density models, priors, and mass point estimates. WL mass differs from true mass due to, e.g., the intrinsic ellipticity of sources, correlated or uncorrelated matter and large-scale structure, halo triaxiality and orientation, and merging or irregular morphology. In an ideal scenario without observational or measurement errors, the maximum likelihood estimator is the most accurate, with WL masses biased low by $\langle b_M \rangle = -14.6 \pm 1.7 \, \%$ on average over the full range $M_\text{200c} > 5 \times 10^{13} \, M_\odot$ and $z < 1$. Due to the stabilising effect of the prior, the biweight, mean, and median estimates are more precise. The scatter decreases with increasing mass and informative priors significantly reduce the scatter. Halo mass density profiles with a truncation provide better fits to the lensing signal, while the accuracy and precision are not significantly affected. We further investigate the impact of additional sources of systematic uncertainty on the WL mass, namely the impact of photometric redshift uncertainties and source selection, the expected performance of \Euclid cluster detection algorithms, and the presence of masks. Taken in isolation, we find that the largest effect is induced by non-conservative source selection. This effect can be mostly removed with a robust selection. As a final \Euclid-like test, we combine systematic effects in a realistic observational setting and find results similar to the ideal case, $\langle b_M \rangle = - 15.5 \pm 2.4 \, \%$, under a robust selection.

astro-ph.CO↗

arXiv2024

Euclid: Field-level inference of primordial non-Gaussianity and cosmic initial conditions

A primary target of the \Euclid space mission is to constrain early-universe physics by searching for deviations from a primordial Gaussian random field. A significant detection of primordial non-Gaussianity would rule out the simplest models of cosmic inflation and transform our understanding of the origin of the Universe. This paper forecasts how well field-level inference of galaxy redshift surveys can constrain the amplitude of local primordial non-Gaussianity ($f_{NL}$), within a Bayesian hierarchical framework, in the upcoming \Euclid data. We design and simulate mock data sets and perform Markov chain Monte Carlo analyses using a full-field forward modelling approach. By including the formation history of the cosmic matter field in the analysis, the method takes into account all available probes of primordial non-Gaussianity, and goes beyond statistical summary estimators of $f_{NL}$. Probes include, for example, two-point and higher-order statistics, peculiar velocity fields, and scale-dependent galaxy biases. Furthermore, the method simultaneously handles systematic survey effects, such as selection effects, survey geometries, and galaxy biases. The forecast shows that the method can reach precision levels of up to $σ(f_{NL}) = 2.3$ (68.3\% CI, and at the grid resolution $ΔL = 62.5\,h^{-1}$Mpc) with \Euclid data. We also provide data products, including realistic $N$-body simulations with nonzero values of $f_{NL}$ and maps of adiabatic curvature fluctuations. The results underscore the feasibility and advantages of field-level inference to constrain $f_{NL}$ in galaxy redshift surveys. Our approach consistently captures all the information available in the large-scale structure to constrain $f_{NL}$, and resolves the degeneracy between early-universe physics and late-time gravitational effects, while mitigating the impact of systematic and observational effects.

astro-ph.CO↗

arXiv2024

Euclid preparation. LII. Forecast impact of super-sample covariance on 3x2pt analysis with Euclid

Deviations from Gaussianity in the distribution of the fields probed by large-scale structure surveys generate additional terms in the data covariance matrix, increasing the uncertainties in the measurement of the cosmological parameters. Super-sample covariance (SSC) is among the largest of these non-Gaussian contributions, with the potential to significantly degrade constraints on some of the parameters of the cosmological model under study - especially for weak lensing cosmic shear. We compute and validate the impact of SSC on the forecast uncertainties on the cosmological parameters for the Euclid photometric survey, obtained with a Fisher matrix analysis, both considering the Gaussian covariance alone and adding the SSC term - computed through the public code $\tt{PySSC}$. The photometric probes are considered in isolation and combined in the '3$\times$2pt' analysis. We find the SSC impact to be non-negligible - halving the Figure of Merit of the dark energy parameters $(w_0, w_a)$ in the 3$\times$2pt case and substantially increasing the uncertainties on $Ω_{{\rm m}, 0}, w_0$, and $σ_8$ for cosmic shear; photometric galaxy clustering, on the other hand, is less affected due to the lower probe response. The relative impact of SSC does not show significant changes under variations of the redshift binning scheme, while it is smaller for weak lensing when marginalising over the multiplicative shear bias nuisance parameters, which also leads to poorer constraints on the cosmological parameters. Finally, we explore how the use of prior information on the shear and galaxy bias changes the SSC impact. Improving shear bias priors does not have a significant impact, while galaxy bias must be calibrated to sub-percent level to increase the Figure of Merit by the large amount needed to achieve the value when SSC is not included.

astro-ph.CO↗

arXiv2024

Euclid preparation. LIII. LensMC, weak lensing cosmic shear measurement with forward modelling and Markov Chain Monte Carlo sampling

LensMC is a weak lensing shear measurement method developed for Euclid and Stage-IV surveys. It is based on forward modelling in order to deal with convolution by a point spread function (PSF) with comparable size to many galaxies; sampling the posterior distribution of galaxy parameters via Markov Chain Monte Carlo; and marginalisation over nuisance parameters for each of the 1.5 billion galaxies observed by Euclid. We quantified the scientific performance through high-fidelity images based on the Euclid Flagship simulations and emulation of the Euclid VIS images; realistic clustering with a mean surface number density of 250 arcmin$^{-2}$ ($I_{\rm E}<29.5$) for galaxies, and 6 arcmin$^{-2}$ ($I_{\rm E}<26$) for stars; and a diffraction-limited chromatic PSF with a full width at half maximum of $0.^{\!\prime\prime}2$ and spatial variation across the field of view. LensMC measured objects with a density of 90 arcmin$^{-2}$ ($I_{\rm E}<26.5$) in 4500 deg$^2$. The total shear bias was broken down into measurement (our main focus here) and selection effects (which will be addressed elsewhere). We found measurement multiplicative and additive biases of $m_1=(-3.6\pm0.2)\times10^{-3}$, $m_2=(-4.3\pm0.2)\times10^{-3}$, $c_1=(-1.78\pm0.03)\times10^{-4}$, $c_2=(0.09\pm0.03)\times10^{-4}$; a large detection bias with a multiplicative component of $1.2\times10^{-2}$ and an additive component of $-3\times10^{-4}$; and a measurement PSF leakage of $α_1=(-9\pm3)\times10^{-4}$ and $α_2=(2\pm3)\times10^{-4}$. When model bias is suppressed, the obtained measurement biases are close to Euclid requirement and largely dominated by undetected faint galaxies ($-5\times10^{-3}$). Although significant, model bias will be straightforward to calibrate given the weak sensitivity. LensMC is publicly available at https://gitlab.com/gcongedo/LensMC

astro-ph.CO↗

arXiv2024

Euclid and KiDS-1000: Quantifying the impact of source-lens clustering on cosmic shear analyses

The transition from current Stage-III surveys such as the Kilo-Degree Survey (KiDS) to the increased area and redshift range of Stage IV surveys such as Euclid will significantly increase the precision of weak lensing analyses. However, with increasing precision, the accuracy of model assumptions needs to be evaluated. In this study, we quantify the impact of the correlated clustering of weak lensing source galaxies with the surrounding large-scale structure, known as source-lens clustering (SLC), which is commonly neglected. For this, we use simulated cosmological datasets with realistically distributed galaxies and measure shear correlation functions for both clustered and uniformly distributed source galaxies. Cosmological analyses are performed for both scenarios to quantify the impact of SLC on parameter inference for a KiDS-like and a Euclid-like setting. We find for Stage III surveys, SLC has a minor impact when accounting for nuisance parameters for intrinsic alignments and shifts of tomographic bins, as these nuisance parameters absorb the effect of SLC, thus changing their original meaning. For KiDS (Euclid), the inferred intrinsic alignment amplitude $A_{IA}$ changes from $0.11_{-0.46}^{+0.44}$ ($-0.009_{-0.080}^{+0.079}$) for data without SLC to $0.28_{-0.44}^{+0.42}$ ($0.022_{-0.082}^{+0.081}$) with SLC. However, fixed nuisance parameters lead to shifts in $S_8$ and $Ω_{m}$, emphasizing the need for including SLC in the modelling. For Euclid, we find that $σ_8$, $Ω_m$, and $w_0$ are shifted by $0.19$, $0.12$, and $0.12\, σ$, respectively, when including free nuisance parameters, and by $0.20$, $0.16$, and $0.32\,σ$ when fixing the nuisance parameters. Consequently, SLC on its own has only a small impact on the inferred parameter inference when using uninformative priors for nuisance parameters.

astro-ph.CO↗

arXiv2024

Euclid preparation. LIX. Angular power spectra from discrete observations

We present the framework for measuring angular power spectra in the Euclid mission. The observables in galaxy surveys, such as galaxy clustering and cosmic shear, are not continuous fields, but discrete sets of data, obtained only at the positions of galaxies. We show how to compute the angular power spectra of such discrete data sets, without treating observations as maps of an underlying continuous field that is overlaid with a noise component. This formalism allows us to compute exact theoretical expectations for our measured spectra, under a number of assumptions that we track explicitly. In particular, we obtain exact expressions for the additive biases ("shot noise") in angular galaxy clustering and cosmic shear. For efficient practical computations, we introduce a spin-weighted spherical convolution with a well-defined convolution theorem, which allows us to apply exact theoretical predictions to finite-resolution maps, including HEALPix. When validating our methodology, we find that our measurements are biased by less than 1% of their statistical uncertainty in simulations of Euclid's first data release.

astro-ph.CO↗