arXiv subjects

L. Linke

Publications and source records attributed to L. Linke.

10 recordsLinked to original sources

arXiv2026

KiDS-Legacy: Joint analysis of second- and third-order cosmic shear

Weak lensing by large-scale structure is a powerful cosmological probe. While most analyses rely on second-order correlations, these are primarily sensitive to the parameter combination $S_8 = \sigma_8 (\Omega_m/0.3)^{0.5}$, limiting their ability to constrain $\Omega_m$ and other cosmological parameters independently. Higher-order statistics capture non-Gaussian features of the density field and can therefore break parameter degeneracies and extract more cosmological information from weak lensing surveys. We present a joint analysis of second- and third-order cosmic shear in the final data release of the Kilo-Degree Survey (KiDS-Legacy). We combine COSEBIs (Complete Orthogonal Sets of E-/B-mode Integrals) at scales between 2' and 300' with third-order aperture mass moments at scales between 4' and 32' to perform a joint analysis of second- and third-order statistics. Compared to previous KiDS analyses, we implement several methodological advances: an intrinsic alignment model with redshift and mass dependence, a baryon correction model validated on multiple hydrodynamical simulations, and corrections for reduced shear and source clustering. Combining COSEBIs with third-order aperture mass statistics in KiDS-Legacy yields $\Omega_m = 0.297^{+0.056}_{-0.040}$ and $S_8 = 0.806^{+0.025}_{-0.023}$, significantly tightening the $\Omega_m$ constraints and more than doubling the figure of merit in the $\Omega_m$--$S_8$ plane compared to the two-point analysis alone. The third-order measurements pass stringent internal consistency tests, are fully compatible with the KiDS-Legacy 2-point constraints, other 2+3-point lensing results and with Planck CMB measurements within $1\sigma$, providing no evidence for an $S_8$ tension and demonstrating the maturity of 3-point cosmic shear as a key probe for forthcoming surveys.

astro-ph.CO↗

arXiv2025

Euclid preparation. LXXXV. Toward a DR1 application of higher-order weak lensing statistics

This is the second paper in the HOWLS (higher-order weak lensing statistics) series exploring the usage of non-Gaussian statistics for cosmology inference within Euclid. With respect to our first paper, we develop a full tomographic analysis based on realistic photometric redshifts that allows us to derive Fisher forecasts in the ($\sigma_8$, $w_0$) plane for a Euclid-like data release 1 (DR1) setup. We find that the five higher-order statistics (HOS) that satisfy the Gaussian likelihood assumption of the Fisher formalism (one-point probability distribution function, $\ell$1-norm, peak counts, Minkowski functionals, and Betti numbers) each outperform the shear two-point correlation functions by a factor of $2.5$ on the $w_0$ forecasts, with only marginal improvement when used in combination with two-point estimators, suggesting that every HOS is able to retrieve both the non-Gaussian and Gaussian information of the matter density field. The similar performance of the different estimators is explained by a homogeneous use of multi-scale and tomographic information, optimized to lower computational costs. These results hold for the three mass mapping techniques of the Euclid pipeline, aperture mass, Kaiser--Squires, and Kaiser--Squires plus, and they are unaffected by the application of realistic star masks. Finally, we explored the use of HOS with the Bernardeau--Nishimichi--Taruya (BNT) nulling scheme approach, finding promising results toward applying physical scale cuts to HOS.

astro-ph.CO↗

arXiv2025

Non-linear infusion of intrinsic alignment and source clustering: impact on non-Gaussian cosmic shear statistics

Intrinsic alignments (IA) of galaxies is one of the key secondary signals to cosmic shear measurements, and must be modeled to interpret weak lensing data and infer the correct cosmology. There are large uncertainties in the physical description of IA, and analytical calculations are often out of reach for weak lensing statistics beyond two-point functions. We present here a set of six flexible IA models infused directly into weak lensing simulations, constructed from the mass shells, the projected tidal fields and, optionally, dark matter halo catalogues. We start with the non-linear linear alignment (NLA) and progressively sophisticate the galaxy bias and the tidal coupling models, including the commonly-used extended NLA (also known as the e-NLA or $\delta$-NLA) and the tidal torque (TT) models. We validate our methods with MCMC analyses from two-point shear statistics, then compute the impact on non-Gaussian cosmic shear probes from these catalogues as well as from reconstructed convergence maps. We find that the $\delta$-NLA model has by far the largest impact on most probes, at times more than twice the strength of the NLA. We also observe large differences between the IA models in under-dense regions, which makes minima, void profiles and lensing PDF the best probes for model rejection. Furthermore, our bias models allow us to separately study the source-clustering term for each of these probes, finding good agreement with the existing literature, and extending the results to these new probes. The third-order aperture mass statistics ($M^3_{ap}$) and the integrated three-point functions are particularly sensitive to this when including low-redshift data, often exceeding a 20% impact on the data vector. Our IA models are straightforward to implement and rescale from a single simulated IA-infused galaxy catalogue, allowing for fast model exploration.

astro-ph.CO↗

arXiv2025

Euclid: Early Release Observations. Weak gravitational lensing analysis of Abell 2390

The Euclid space telescope of the European Space Agency (ESA) is designed to provide sensitive and accurate measurements of weak gravitational lensing distortions over wide areas on the sky. Here we present a weak gravitational lensing analysis of early Euclid observations obtained for the field around the massive galaxy cluster Abell 2390 as part of the Euclid Early Release Observations programme. We conduct galaxy shape measurements using three independent algorithms (LensMC, KSB+, and SourceXtractor++). Incorporating multi-band photometry from Euclid and Subaru/Suprime-Cam, we estimate photometric redshifts to preferentially select background sources from tomographic redshift bins, for which we calibrate the redshift distributions using the self-organising map approach and data from the Cosmic Evolution Survey (COSMOS). We quantify the residual cluster member contamination and correct for it in bins of photometric redshift and magnitude using their source density profiles, including corrections for source obscuration and magnification. We reconstruct the cluster mass distribution and jointly fit the tangential reduced shear profiles of the different tomographic bins with spherical Navarro--Frenk--White profile predictions to constrain the cluster mass, finding consistent results for the three shape catalogues and good agreement with earlier measurements. As an important validation test we compare these joint constraints to mass measurements obtained individually for the different tomographic bins, finding good consistency. More detailed constraints on the cluster properties are presented in a companion paper that additionally incorporates strong lensing measurements. Our analysis provides a first demonstration of the outstanding capabilities of Euclid for tomographic weak lensing measurements.

astro-ph.CO↗

arXiv2025

Euclid: An emulator for baryonic effects on the matter bispectrum

Understanding the impact of baryonic processes such as star formation and active galactic nuclei (AGN) feedback on matter clustering is crucial to ensure precise and unbiased cosmological inference. Most theoretical models of baryonic effects to date focus on two-point statistics, neglecting higher-order contributions. This work develops a fast and accurate emulator for baryonic effects on the matter bispectrum, a key non-Gaussian statistic in the nonlinear regime. We employ high-resolution $N$-body simulations from the BACCO suite and apply a combination of cutting-edge techniques such as cosmology scaling and baryonification to efficiently span a large cosmological and astrophysical parameter space. A deep neural network is trained to emulate baryonic effects on the matter bispectrum measured in simulations, capturing modifications across various scales and redshifts relevant to Euclid. We validate the emulator accuracy and robustness using an analysis of \Euclid mock data, employing predictions from the state-of-the-art FLAMINGO hydrodynamical simulations. The emulator reproduces baryonic suppression in the bispectrum to better than 2$\%$ for the $68\%$ percentile across most triangle configurations for $k \in [0.01, 20]\,\mathrm{i}h\mathrm{Mpc}^{-1}$ and ensures consistency between cosmological posteriors inferred from second- and third-order weak lensing statistics. These results demonstrate that our emulator meets the high-precision requirements of the Euclid mission for at least the first data release and provides reliable forecasts of the cosmological information contained in the small-scale matter bispectrum. This underscores the potential of emulation techniques to bridge the gap between complex baryonic physics and observational data, maximising the scientific output of Euclid.

astro-ph.CO↗

arXiv2024

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 S\'ersic 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-S\'ersic 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-S\'ersic 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↗

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 $\Omega_{m}$, emphasizing the need for including SLC in the modelling. For Euclid, we find that $\sigma_8$, $\Omega_m$, and $w_0$ are shifted by $0.19$, $0.12$, and $0.12\, \sigma$, respectively, when including free nuisance parameters, and by $0.20$, $0.16$, and $0.32\,\sigma$ 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. V. The Flagship galaxy mock catalogue: a comprehensive simulation for the Euclid mission

We present the Flagship galaxy mock, a simulated catalogue of billions of galaxies designed to support the scientific exploitation of the Euclid mission. Euclid is a medium-class mission of the European Space Agency optimised to determine the properties of dark matter and dark energy on the largest scales of the Universe. It probes structure formation over more than 10 billion years primarily from the combination of weak gravitational lensing and galaxy clustering data. The breath of Euclid's data will also foster a wide variety of scientific analyses. The Flagship simulation was developed to provide a realistic approximation to the galaxies that will be observed by Euclid and used in its scientific analyses. We ran a state-of-the-art N-body simulation with four trillion particles, producing a lightcone on the fly. From the dark matter particles, we produced a catalogue of 16 billion haloes in one octant of the sky in the lightcone up to redshift z=3. We then populated these haloes with mock galaxies using a halo occupation distribution and abundance matching approach, calibrating the free parameters of the galaxy mock against observed correlations and other basic galaxy properties. Modelled galaxy properties include luminosity and flux in several bands, redshifts, positions and velocities, spectral energy distributions, shapes and sizes, stellar masses, star formation rates, metallicities, emission line fluxes, and lensing properties. We selected a final sample of 3.4 billion galaxies with a magnitude cut of H_E<26, where we are complete. We have performed a comprehensive set of validation tests to check the similarity to observational data and theoretical models. In particular, our catalogue is able to closely reproduce the main characteristics of the weak lensing and galaxy clustering samples to be used in the mission's main cosmological analysis. (abridged)

astro-ph.CO↗

arXiv2024

Euclid -- The Dark Universe detective

Euclid is a recently launched medium-class mission by the European Space Agency (ESA) designed to measure cosmological parameters, test the cosmological standard model, and explore the nature of dark matter and dark energy. To this end, Euclid conducts a survey of up to 14000 square degrees of the extra-galactic sky and obtains optical and near-infrared photometric measurements for more than a billion galaxies as well as near-infrared slitless spectroscopy for more than 35 million galaxies. These observations will be used to estimate galaxy clustering and cosmic shear. It is expected that Euclid will achieve percent-level constraints on the Dark Energy equation of state parameter. The survey will also be exploited with a range of other cosmological probes and prove revolutionary for non-cosmological science.

astro-ph.CO↗

arXiv2023

Euclid Preparation. XXVIII. Forecasts for ten different higher-order weak lensing statistics

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale structure. The aim of the Higher-Order Weak Lensing Statistics (HOWLS) project is to assess, compare, and combine the constraining power of ten different HOS on a common set of $Euclid$-like mocks, derived from N-body simulations. In this first paper of the HOWLS series, we computed the nontomographic ($\Omega_{\rm m}$, $\sigma_8$) Fisher information for the one-point probability distribution function, peak counts, Minkowski functionals, Betti numbers, persistent homology Betti numbers and heatmap, and scattering transform coefficients, and we compare them to the shear and convergence two-point correlation functions in the absence of any systematic bias. We also include forecasts for three implementations of higher-order moments, but these cannot be robustly interpreted as the Gaussian likelihood assumption breaks down for these statistics. Taken individually, we find that each HOS outperforms the two-point statistics by a factor of around two in the precision of the forecasts with some variations across statistics and cosmological parameters. When combining all the HOS, this increases to a $4.5$ times improvement, highlighting the immense potential of HOS for cosmic shear cosmological analyses with $Euclid$. The data used in this analysis are publicly released with the paper.

astro-ph.CO↗