arXiv subjects

M. Martinelli

Publications and source records attributed to M. Martinelli.

At least 73 records · Page 4Linked to original sources

arXiv2025

Euclid Structural-Thermal-Optical Performance

The Euclid system performance is defined in terms of image quality metrics tuned to the weak gravitational lensing (WL) cosmological probe. WL induces stringent requirements on the shape and stability of the VIS instrument system point spread function (PSF). The PSF is affected by error contributions from the telescope, the focal plane and image motion, and is controlled by a global error budget with error allocations to each contributor. Aims. During spacecraft development, we verified through a structural-thermal-optical performance (STOP) analysis that the built and verified telescope with its spacecraft interface meets the in-orbit steady-state and transient image quality requirements. Methods. For the purposes of the STOP analysis, a detailed finite-element mathematical model was set up and a standard set of test cases, both steady-state and transient, was defined, comprising combinations of worst-case boundary conditions. Results. The STOP analysis addressed the interaction of all spacecraft components in transmitting temperature-induced loads that lead to optical train deformation. The results of the prelaunch analysis demonstrated that temperature-induced optical perturbations will be well below the allowable limits for all permitted observing conditions. During the first year in orbit, we used the STOP analysis predictions to help interpret the measured performance as a function of environmental variables. Unpredicted disturbances were discovered and unexpected sensitivities were revealed. In-orbit temperature variations are small (<300 mK) and so are their effects on the telescope structure, but they are detected in the time histories of the image quality metrics and are a non-negligible factor in the PSF stability budget demanded by the WL science. Taking everything into account, our analysis confirms the excellent overall performance of the telescope.

astro-ph.IM↗

arXiv2025

Euclid preparation: LXXXI. The impact of nonparametric star formation histories on spatially resolved galaxy property estimation using synthetic Euclid images

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 SFHs from Euclid-like data. This study provides a proof of concept for extracting the spatially resolved SFHs of local galaxies with Euclid, highlighting the strengths and limitations of SFH modeling in the context of next-generation galaxy surveys. We used the spectral energy distribution (SED) fitting code Prospector to model both spatially resolved and global SFHs using parametric and nonparametric configurations. The input consisted of mock ultraviolet--near-infrared photometry derived from the TNG50 cosmological simulation and processed with the radiative transfer code SKIRT. We show that nonparametric SFHs provide a more effective approach to mitigating the outshining effect by recent star formation, offering improved accuracy in the determination of galaxy stellar properties. Also, we find that the nonparametric SFH model at resolved scales closely recovers the stellar mass formation times (within 0.1~dex) and the ground truth values from TNG50, with an absolute average bias of $0.03$~dex in stellar mass and $0.01$~dex in both specific star formation rate and mass-weighted age. In contrast, larger offsets are estimated for all stellar properties and formation times when using a simple $τ$-model SFH, at both resolved and global scales, highlighting its limitations. These results emphasize the critical role of nonparametric SFHs in both global and spatially resolved analyses, as they better capture the complex evolutionary pathways of galaxies and avoid the biases inherent in simple parametric models.

astro-ph.GA↗

arXiv2025

\textit{Euclid}: From Galaxies to Gravitational Waves -- Forecasting Stochastic Gravitational Wave Background Anisotropies and Their Cross-Correlation

We estimate the amplitude and spatial anisotropy in the stochastic gravitational wave background (SGWB) energy density due to compact binary coalescence (CBC) events: binary black holes (BBH), binary neutron stars (BNS), and black hole-neutron star (BHNS) mergers. Our starting point is the Flagship Simulation Galaxy Catalogue developed by the Euclid Consortium. For each galaxy in the Catalogue, we use the simulated mass and starformation to constrain the galaxy's star-formation history, and predict its contribution to the gravitational-wave energy density through CBC mergers. Combining such contributions from all galaxies in the Catalogue results in a prediction for the frequency spectrum and spatial anisotropy of the CBC SGWB. We also compare this prediction to semi-analytical models of SGWB generated by compact binaries. We identify a set of effective parameters that capture the key features of these models, and we apply a Bayesian framework to infer these parameters assuming an ideal scenario of cosmic variance-limited search. This represents the first step toward developing a comprehensive framework that will eventually enable the correlation of SGWB anisotropy and \textit{Euclid} galaxy data, potentially allowing us to extract valuable astrophysical information from this new observable.

gr-qc↗

arXiv2025

Euclid: Quick Data Release (Q1) -- Secondary nuclei in early-type galaxies

Massive early-type galaxies (ETGs) are believed to form primarily through mergers of less massive progenitors, leaving behind numerous traces of violent formation histories, such as stellar streams and shells. A particularly striking signature of these mergers is the formation of supermassive black hole (SMBH) binaries, which can create depleted stellar cores through interactions with stars on radial orbits - a process known as core scouring. The secondary SMBH in such systems may still carry a dense stellar envelope and thereby remain observable for some time as a secondary nucleus, while it is sinking towards the shared gravitational potential of the merged galaxy. We leverage Euclid's Q1 Early Release data to systematically search for secondary nuclei in ETGs. We present a preliminary sample of 666 candidate systems distributed over 504 hosts (some of which contain multiple secondary nuclei). The vast majority of these fall at separations of 3 kpc to 15 kpc, indicative of normal mergers. 44 fall at projected separations of less than 2 kpc. We argue those candidates at very close angular separations are unlikely to be a consequence of chance alignments. We show that their stellar masses are mostly too large for them to be globular clusters and that a significant subset are unresolved even at Euclid's spatial resolution, rendering them too small to be dwarf galaxies. These may represent the highest-density nuclei of a previously merged galaxy, currently sinking into the centre of the new, common gravitational potential and thus likely to host a secondary SMBH. We then demonstrate that convolutional neural networks offer a viable avenue to detect multiple nuclei in the thirty-times larger sky coverage of the future Euclid DR1. Finally, we argue that our method could detect the remnants of a recoil event from two merged SMBHs.

astro-ph.GA↗

arXiv2025

Euclid preparation: The flat-sky approximation for the clustering of Euclid's photometric galaxies

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 configuration representing the first data release (DR1) and a 13 bin configuration representative of 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. Contrarily, 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.

astro-ph.CO↗

arXiv2025

Euclid Quick Data Release (Q1). Active galactic nuclei identification using diffusion-based inpainting of Euclid VIS images

Light emission from galaxies exhibit diverse brightness profiles, influenced by factors such as galaxy type, structural features and interactions with other galaxies. Elliptical galaxies feature more uniform light distributions, while spiral and irregular galaxies have complex, varied light profiles due to their structural heterogeneity and star-forming activity. In addition, galaxies with an active galactic nucleus (AGN) feature intense, concentrated emission from gas accretion around supermassive black holes, superimposed on regular galactic light, while quasi-stellar objects (QSO) are the extreme case of the AGN emission dominating the galaxy. The challenge of identifying AGN and QSO has been discussed many times in the literature, often requiring multi-wavelength observations. This paper introduces a novel approach to identify AGN and QSO from a single image. Diffusion models have been recently developed in the machine-learning literature to generate realistic-looking images of everyday objects. Utilising the spatial resolving power of the Euclid VIS images, we created a diffusion model trained on one million sources, without using any source pre-selection or labels. The model learns to reconstruct light distributions of normal galaxies, since the population is dominated by them. We condition the prediction of the central light distribution by masking the central few pixels of each source and reconstruct the light according to the diffusion model. We further use this prediction to identify sources that deviate from this profile by examining the reconstruction error of the few central pixels regenerated in each source's core. Our approach, solely using VIS imaging, features high completeness compared to traditional methods of AGN and QSO selection, including optical, near-infrared, mid-infrared, and X-rays.

astro-ph.GA↗

arXiv2025

Euclid: Exploring observational systematics in cluster cosmology -- a comprehensive analysis of cluster counts and clustering

This study explores the impact of observational and modelling systematic effects on cluster number counts and cluster clustering and provides model prescriptions for their joint analysis, in the context of the \Euclid survey. Using 1000 \Euclid-like cluster catalogues, we investigate the effect of systematic uncertainties on cluster summary statistics and their auto- and cross-covariance, and perform a likelihood analysis to evaluate their impact on cosmological constraints, with a focus on the matter density parameter $Ω_{\rm m}$ and on the power spectrum amplitude $σ_8$. Combining cluster clustering with number counts significantly improves cosmological constraints, with the figure of merit increasing by over 300\% compared to number counts alone. We confirm that the two probes are uncorrelated, and the cosmological constraints derived from their combination are almost insensitive to the cosmology dependence of the covariance. We find that photometric redshift uncertainties broaden cosmological posteriors by 20--30\%, while secondary effects like redshift-space distortions (RSDs) have a smaller impact on the posteriors -- 5\% for clustering alone, 10\% when combining probes -- but can significantly bias the constraints if neglected. We show that clustering data below $60\,h^{-1}\,$Mpc provides additional constraining power, while scales larger than acoustic oscillation scale add almost no information on $Ω_{\rm m}$ and $σ_8$ parameters. RSDs and photo-$z$ uncertainties also influence the number count covariance, with a significant impact, of about 15--20\%, on the parameter constraints.

astro-ph.CO↗

arXiv2025

Euclid preparation. Cosmology Likelihood for Observables in Euclid (CLOE). 6: Impact of systematic uncertainties on the cosmological analysis

Extracting cosmological information from the Euclid galaxy survey will require modelling numerous systematic effects during the inference process. This implies varying a large number of nuisance parameters, which have to be marginalised over before reporting the constraints on the cosmological parameters. This is a delicate process, especially with such a large parameter space, which could result in biased cosmological results. In this work, we study the impact of different choices for modelling systematic effects and prior distribution of nuisance parameters for the final Euclid Data Release, focusing on the 3$\times$2pt analysis for photometric probes and the galaxy power spectrum multipoles for the spectroscopic probes. We explore the effect of intrinsic alignments, linear galaxy bias, magnification bias, multiplicative cosmic shear bias and shifts in the redshift distribution for the photometric probes, as well as the purity of the spectroscopic sample. We find that intrinsic alignment modelling has the most severe impact with a bias up to $6\,σ$ on the Hubble constant $H_0$ if neglected, followed by mis-modelling of the redshift evolution of galaxy bias, yielding up to $1.5\,σ$ on the parameter $S_8\equivσ_8\sqrt{Ω_{\rm m} /0.3}$. Choosing a too optimistic prior for multiplicative bias can also result in biases of the order of $0.7\,σ$ on $S_8$. We also find that the precision on the estimate of the purity of the spectroscopic sample will be an important driver for the constraining power of the galaxy clustering full-shape analysis. These results will help prioritise efforts to improve the modelling and calibration of systematic effects in Euclid.

astro-ph.CO↗

arXiv2025

Cosmology Likelihood for Observables in \Euclid (CLOE). 1. Theoretical recipe

As the statistical precision of cosmological measurements increases, the accuracy of the theoretical description of these measurements needs to increase correspondingly in order to infer the underlying cosmology that governs the Universe. To this end, we have created the Cosmology Likelihood for Observables in Euclid (CLOE), which is a novel cosmological parameter inference pipeline developed within the Euclid Consortium to translate measurements and covariances into cosmological parameter constraints. In this first in a series of six papers, we describe the theoretical recipe of this code for the Euclid primary probes. These probes are composed of the photometric 3x2pt observables of cosmic shear, galaxy-galaxy lensing, and galaxy clustering, along with spectroscopic galaxy clustering. We provide this description in both Fourier and configuration space for standard and extended summary statistics, including the wide range of systematic uncertainties that affect them. This includes systematic uncertainties such as intrinsic galaxy alignments, baryonic feedback, photometric and spectroscopic redshift uncertainties, shear calibration uncertainties, sample impurities, photometric and spectroscopic galaxy biases, as well as magnification bias. The theoretical descriptions are further able to accommodate both Gaussian and non-Gaussian likelihoods and extended cosmologies with non-zero curvature, massive neutrinos, evolving dark energy, and simple forms of modified gravity. These theoretical descriptions that underpin CLOE will form a crucial component in revealing the true nature of the Universe with next-generation cosmological surveys such as Euclid.

astro-ph.CO↗

arXiv2025

Euclid: Forecasts on $Λ$CDM consistency tests with growth rate data

The large-scale structure (LSS) of the Universe is an important probe for deviations from the canonical cosmological constant $Λ$ and cold dark matter ($Λ$CDM) model. A statistically significant detection of any deviations would signify the presence of new physics or the breakdown of any number of the underlying assumptions of the standard cosmological model or possible systematic errors in the data. In this paper, we quantify the ability of the LSS data products of the spectroscopic survey of the Euclid mission, together with other contemporary surveys, to improve the constraints on deviations from $Λ$CDM in the redshift range $0<z<1.75$. We consider both currently available growth rate data and simulated data with specifications from Euclid and external surveys, based on $Λ$CDM and a modified gravity (MoG) model with an evolving Newton's constant (denoted $μ$CDM), and carry out a binning method and a machine learning reconstruction, based on genetic algorithms (GAs), of several LSS null tests. Using the forecast Euclid growth data from the spectroscopic survey in the range $0.95<z<1.75$, we find that in combination with external data products (covering the range $0<z<0.95$), Euclid will be able to improve on current constraints of null tests of the LSS on average by a factor of eight when using a binning method and a factor of six when using the GAs. Our work highlights the need for synergies between Euclid and other surveys, but also the usefulness of statistical analyses, such as GAs, in order to disentangle any degeneracies in the cosmological parameters. Both are necessary to provide tight constraints over an extended redshift range and to probe for deviations from the $Λ$CDM model.

astro-ph.CO↗

arXiv2025

Euclid VI. NISP-P optical ghosts

The Near-Infrared Spectrometer and Photometer (NISP) onboard Euclid includes several optical elements in its path, which introduce artefacts into the data from non-nominal light paths. To ensure uncontaminated source photometry, these artefacts must be accurately accounted for. This paper focuses on two specific optical features in NISP's photometric data (NISP-P): ghosts caused by the telescope's dichroic beamsplitter, and the bandpass filters within the NISP fore-optics. Both ghost types exhibit a characteristic morphology and are offset from the originating stars. The offsets are well modelled using 2D polynomials, with only stars brighter than approximately 10 magnitudes in each filter producing significant ghost contributions. The masking radii for these ghosts depend on both the source-star brightness and the filter wavelength, ranging from 20 to 40 pixels. We present the final relations and models used in the near-infrared (NIR) data pipeline to mask these ghosts for Euclid's Quick Data Release (Q1).

astro-ph.IM↗

arXiv2025

Euclid: Quick Data Release (Q1) -- Watching ICM-selected galaxy clusters with Euclid eyes -- prospects of Euclid data in the context of large SZ and X-ray based surveys

Galaxy clusters detected through their X-ray emission or Sunyaev--Zeldovich effect (SZE), both produced by the intra-cluster medium (ICM), are key probes in cosmological and astrophysical studies. To maximise the scientific return of such surveys, complementary data are required for cluster confirmation and redshift estimation. This is typically provided by wide-field optical and infrared surveys, which are increasingly challenged by ongoing and future ICM-selected samples. In particular, at high redshifts ($z>1$) probed by upcoming SZE-selected samples, current large surveys may be insufficient for reliable confirmation. Deep, high-resolution infrared surveys like Euclid will thus be essential for confirming most high-redshift clusters. We present an analysis of the first sizeable Euclid dataset (Q1), overlapping with several ICM-selected cluster samples. We apply an adaptation of the MCMF cluster confirmation tool to estimate key properties, including redshift and richness, and to predict Euclid's capabilities for high-redshift cluster confirmation. We find promising performance, particularly at high redshifts, while richness estimates at low redshifts ($z<0.4$) are currently limited by Q1 data quality but should improve with future releases. Using MCMF runs on random lines of sight, we predict that Euclid will confirm clusters at $1<z<2$ as effectively as current optical surveys at $z<0.6$, significantly enhancing high-redshift confirmation. SZE-selected samples will thus greatly benefit from Euclid overlap. Among five known high-$z$ SZE clusters in Q1, we identify the highest-redshift jellyfish galaxy candidate to date, EUCLJ035330.86$-$504347.6 in SPT-CLJ0353$-$5043 ($z=1.32$), two massive star-forming galaxies near ACT-CLJ0350.0$-$4819 ($z=1.46$), and strong lensing features in SPT-CLJ0353$-$5043 and SPT-CLJ0421$-$4845.

astro-ph.CO↗

arXiv2025

Euclid: Relativistic effects in the dipole of the 2-point correlation function

Gravitational redshift and Doppler effects give rise to an antisymmetric component of the galaxy correlation function when cross-correlating two galaxy populations or two different tracers. In this paper, we assess the detectability of these effects in the Euclid spectroscopic galaxy survey. We model the impact of gravitational redshift on the observed redshift of galaxies in the Flagship mock catalogue using a Navarro-Frenk-White profile for the host haloes. We isolate these relativistic effects, largely subdominant in the standard analysis, by splitting the galaxy catalogue into two populations of faint and bright objects and estimating the dipole of their cross-correlation in four redshift bins. In the simulated catalogue, we detect the dipole signal on scales below $30\,h^{-1}{\rm Mpc}$, with detection significances of $4\,σ$ and $3\,σ$ in the two lowest redshift bins, respectively. At higher redshifts, the detection significance drops below $2\,σ$. Overall, we estimate the total detection significance in the Euclid spectroscopic sample to be approximately $6\,σ$. We find that on small scales, the major contribution to the signal comes from the nonlinear gravitational potential. Our study on the Flagship mock catalogue shows that this observable can be detected in Euclid Data Release 2 and beyond.

astro-ph.CO↗

arXiv2025

Euclid preparation. Constraining parameterised models of modifications of gravity with the spectroscopic and photometric primary probes

The Euclid mission has the potential to understand the fundamental physical nature of late-time cosmic acceleration and, as such, of deviations from the standard cosmological model, LCDM. In this paper, we focus on model-independent methods to modify the evolution of scalar perturbations at linear scales. We consider two approaches: the first is based on the two phenomenological modified gravity (PMG) parameters, $μ_{\rm mg}$ and $Σ_{\rm mg}$, which are phenomenologically connected to the clustering of matter and weak lensing, respectively; and the second is the effective field theory (EFT) of dark energy and modified gravity, which we use to parameterise the braiding function, $α_{\rm B}$, which defines the mixing between the metric and the dark energy field. We discuss the predictions from spectroscopic and photometric primary probes by Euclid on the cosmological parameters and a given set of additional parameters featuring the PMG and EFT models. We use the Fisher matrix method applied to spectroscopic galaxy clustering (GCsp), weak lensing (WL), photometric galaxy clustering (GCph), and cross-correlation (XC) between GCph and WL. For the modelling of photometric predictions on nonlinear scales, we use the halo model to cover two limits for the screening mechanism: the unscreened (US) case, for which the screening mechanism is not present; and the super-screened (SS) case, which assumes strong screening. We also assume scale cuts to account for our uncertainties in the modelling of nonlinear perturbation evolution. We choose a time-dependent form for $\{μ_{\rm mg},Σ_{\rm mg}\}$, with two fiducial sets of values for the corresponding model parameters at the present time, $\{\barμ_0,\barΣ_0\}$, and two forms for $α_{\rm B}$, with one fiducial set of values for each of the model parameters, $α_{\rm B,0}$ and $\{α_{\rm B,0},m\}$. (Abridged)

astro-ph.CO↗

arXiv2025

Euclid: Early Release Observations -- The surface brightness and colour profiles of the far outskirts of galaxies in the Perseus cluster

The Perseus field captured by Euclid as part of its Early Release Observations provides a unique opportunity to study cluster environment ranging from outskirts to dense regions. Leveraging unprecedented optical and near-infrared depths, we investigate the stellar structure of massive disc galaxies in this field. This study focuses on outer disc profiles, including simple exponential (Type I), down- (Type II) and up-bending break (Type III) profiles, and their associated colour gradients, to trace late assembly processes across various environments. Type II profiles, though relatively rare in high dense environments, appear stabilised by internal mechanisms like bars and resonances, even within dense cluster cores. Simulations suggest that in dense environments, Type II profiles tend to evolve into Type I profiles over time. Type III profiles often exhibit small colour gradients beyond the break, hinting at older stellar populations, potentially due to radial migration or accretion events. We analyse correlations between galaxy mass, morphology, and profile types. Mass distributions show weak trends of decreasing mass from the centre to the outskirts of the Perseus cluster. Type III profiles become more prevalent, while Type I profiles decrease in lower-mass galaxies with cluster centric distance. Type I profiles dominate in spiral galaxies, while Type III profiles are more common in S0 galaxies. Type II profiles are consistently observed across all morphological types. While the limited sample size restricts statistical power, our findings shed light on the mechanisms shaping galaxy profiles in cluster environments. Future work should extend observations to the cluster outskirts to enhance statistical significance. Additionally, 3D velocity maps are needed to achieve a non-projected view of galaxy positions, offering deeper insights into spatial distribution and dynamics.

astro-ph.GA↗

arXiv2025

Euclid preparation LXXI. Simulations and nonlinearities beyond $\mathsfΛ$CDM. 3. Constraints on $f(R)$ models from the photometric primary probes

We study the constraint on $f(R)$ gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the Hu-Sawicki $f(R)$ gravity model, we consider four different predictions for the ratio between the power spectrum in $f(R)$ and that in $Λ$CDM: a fitting formula, the halo model reaction approach, ReACT and two emulators based on dark matter only $N$-body simulations, FORGE and e-Mantis. These predictions are added to the MontePython implementation to predict the angular power spectra for weak lensing (WL), photometric galaxy clustering and their cross-correlation. By running Markov Chain Monte Carlo, we compare constraints on parameters and investigate the bias of the recovered $f(R)$ parameter if the data are created by a different model. For the pessimistic setting of WL, one dimensional bias for the $f(R)$ parameter, $\log_{10}|f_{R0}|$, is found to be $0.5 σ$ when FORGE is used to create the synthetic data with $\log_{10}|f_{R0}| =-5.301$ and fitted by e-Mantis. The impact of baryonic physics on WL is studied by using a baryonification emulator BCemu. For the optimistic setting, the $f(R)$ parameter and two main baryon parameters are well constrained despite the degeneracies among these parameters. However, the difference in the nonlinear dark matter prediction can be compensated by the adjustment of baryon parameters, and the one-dimensional marginalised constraint on $\log_{10}|f_{R0}|$ is biased. This bias can be avoided in the pessimistic setting at the expense of weaker constraints. For the pessimistic setting, using the $Λ$CDM synthetic data for WL, we obtain the prior-independent upper limit of $\log_{10}|f_{R0}|< -5.6$. Finally, we implement a method to include theoretical errors to avoid the bias.

astro-ph.CO↗

arXiv2025

Euclid preparation. Estimating galaxy physical properties using CatBoost chained regressors with attention

Euclid will image ~14000 deg^2 of the extragalactic sky at visible and NIR wavelengths, providing a dataset of unprecedented size and richness that will facilitate a multitude of studies into the evolution of galaxies. In the vast majority of cases the main source of information will come from broad-band images and data products thereof. Therefore, there is a pressing need to identify or develop scalable yet reliable methodologies to estimate the redshift and physical properties of galaxies using broad-band photometry from Euclid, optionally including ground-based optical photometry also. To address this need, we present a novel method to estimate the redshift, stellar mass, star-formation rate, specific star-formation rate, E(B-V), and age of galaxies, using mock Euclid and ground-based photometry. The main novelty of our property-estimation pipeline is its use of the CatBoost implementation of gradient-boosted regression-trees, together with chained regression and an intelligent, automatic optimization of the training data. The pipeline also includes a computationally-efficient method to estimate prediction uncertainties, and, in the absence of ground-truth labels, provides accurate predictions for metrics of model performance up to z~2. We apply our pipeline to several datasets consisting of mock Euclid broad-band photometry and mock ground-based ugriz photometry, to evaluate the performance of our methodology for estimating the redshift and physical properties of galaxies detected in the Euclid Wide Survey. The quality of our photometric redshift and physical property estimates are highly competitive overall, validating our modeling approach. We find that the inclusion of ground-based optical photometry significantly improves the quality of the property estimation, highlighting the importance of combining Euclid data with ancillary ground-based optical data. (Abridged)

astro-ph.GA↗

arXiv2025

Euclid preparation. LXVII. Deep learning true galaxy morphologies for weak lensing shear bias calibration

To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double Sérsic profile, neglecting the influence of galaxy substructures and morphologies deviating from such a simplified parametric characterization. While this approximation may be sufficient for previous data sets, the stringent cosmic shear calibration requirements and the high quality of the data in the upcoming Euclid survey demand a consideration of the effects that realistic galaxy substructures have on shear measurement biases. Here we present a novel deep learning-based method to create such simulated galaxies directly from HST data. We first build and validate a convolutional neural network based on the wavelet scattering transform to learn noise-free representations independent of the point-spread function of HST galaxy images that can be injected into simulations of images from Euclid's optical instrument VIS without introducing noise correlations during PSF convolution or shearing. Then, we demonstrate the generation of new galaxy images by sampling from the model randomly and conditionally. Next, we quantify the cosmic shear bias from complex galaxy shapes in Euclid-like simulations by comparing the shear measurement biases between a sample of model objects and their best-fit double-Sérsic counterparts. Using the KSB shape measurement algorithm, we find a multiplicative bias difference between these branches with realistic morphologies and parametric profiles on the order of $6.9\times 10^{-3}$ for a realistic magnitude-Sérsic index distribution. Moreover, we find clear detection bias differences between full image scenes simulated with parametric and realistic galaxies, leading to a bias difference of $4.0\times 10^{-3}$ independent of the shape measurement method. This makes it relevant for stage IV weak lensing surveys such as Euclid.

astro-ph.CO↗