arXiv subjects

E. Tsaprazi

Publications and source records attributed to E. Tsaprazi.

5 recordsLinked to original sources

arXiv2026

Euclid: Survey mask effects on clustering of galaxy clusters

Wide-area cluster catalogues from Stage-IV surveys will substantially improve the precision of cluster clustering measurements, making the control of observational systematic effects essential for cosmological inference. In preparation for the first Euclid data release (DR1), we assess the impact of the survey mask and non-homogeneous sky coverage on the two-point correlation function of galaxy clusters and its covariance. Using DR1-like lightcone mocks, we confirm that the irregular footprint does not introduce appreciable changes in the two-point correlation function when the same mask is applied to the random catalogue. We also find that spatial inhomogeneities, implemented as variations of the cluster selection function in different patches of the sky, do not significantly bias the clustering amplitude, up to levels of variation well above those expected for DR1. When the degree of inhomogeneity is increased to the regime where the effect becomes significant, we show that its amplitude is related to the maximum variation of the selection function among different regions, rather than to the number of such regions. We further find that irregular mask geometry and non-uniform sky coverage both increase the clustering covariance, introducing small, nearly scale-independent offsets that can be captured by nuisance parameters in the covariance model. Our results consolidate the treatment of mask systematic errors for DR1 and inform the methodological refinements required for future \Euclid cluster cosmology.

astro-ph.CO↗

arXiv2026

Euclid: Modelling observational effects in cluster counts and cluster 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 investigated the effect of systematic uncertainties on cluster summary statistics and their auto- and cross-covariance, and performed 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 such as 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 the acoustic oscillation scale add almost no information on $Ω_{\rm m}$ and $σ_8$ parameters. The 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↗

arXiv2026

Euclid preparation. XCI. Validation method for the detections in the Euclid Catalogue of Galaxy Clusters using external data

We present our methodology for identifying known clusters as counterparts to objects in the Euclid Catalogue of Galaxy Clusters (ECGC). Euclid is expected to detect a large number of optically-selected galaxy clusters over the approximately 14000 square degrees of its extragalactic sky survey. Extending out well beyond redshift unity, the catalogue will contain many new high-redshift clusters, while at lower redshifts a fraction of the clusters will have been observed in other surveys. Identifying these known clusters as counterparts to the Euclid-detected clusters is an important step in the validation and construction of the ECGC to augment information with external observables. We present a set of catalogues and meta-catalogues of known clusters that we have assembled for this step, and we illustrate their application and our methodology using the Dark Energy Survey Year 1 RedMaPPer cluster catalogue in lieu of the future ECGC. In the process of this work, we have constructed and delivered an updated EC-RedMaPPer catalogue with multi-wavelength counterparts.

astro-ph.CO↗

arXiv2026

Euclid preparation. Testing template-fitting models for the multipoles of the two-point clustering of galaxy clusters

The Euclid satellite will deliver a catalogue of optically selected galaxy clusters spanning from around 2000 deg$^2$ in Data Release (DR) 1 to around $14\,000$ deg$^2$ in DR3. In this work, we assess the validity of cluster clustering (CC) models for template-fitting, which complements the full-shape methodology by providing cosmological information from the anisotropy of the redshift-space two-point correlation function (2PCF). Both methods will be used to analyse the cluster 2PCF multipoles with Euclid. We examined the multipoles of the two-point redshift-space clustering of galaxy clusters simulated with the semi-analytic PINOCCHIO code using third-order Lagrangian perturbation theory, assuming a Euclid DR1-like footprint of 500 deg$^2$ in the northern hemisphere and 1400 deg$^2$ in the southern hemisphere. We estimated the first three even multipoles of the 2PCF and associated covariance matrix from 1000 DR1-like synthetic catalogues. We studied the impact of modelling the relevant non-linearities, halo bias, and photometric redshift uncertainties on the 2PCF. We applied three clustering models to the mock catalogues at 0 10^{14}\;h^{-1}\,M_\odot$ under realistic and optimistic photometric redshift uncertainty scenarios. We formulated a set of permissive and conservative criteria that ought to be fulfilled by the multipole cut-off scales and validated them against 100 mock catalogues via an inference of the growth rate multiplied by the matter power spectrum normalisation parameter, $fσ_8$. We tested the dispersion, Scoccimarro, and Taruya-Nishimichi-Saito models. We find that the dispersion model yields unbiased inferences on $fσ_8$ from CC down to 10 $h^{-1}$ Mpc in a DR1-like setting. All clustering models provide similar goodness-of-fit metrics in the presence of DR1-like cluster redshift uncertainties.

astro-ph.CO↗

arXiv2025

Euclid preparation. Establishing the quality of the 2D reconstruction of the filaments of the cosmic web with DisPerSE using Euclid photometric redshifts

Cosmic filaments are prominent structures of the matter distribution of the Universe. Modern detection algorithms are an efficient way to identify filaments in large-scale observational surveys of galaxies. Many of these methods were originally designed to work with simulations and/or well-sampled spectroscopic surveys. When spectroscopic redshifts are not available, the filaments of the cosmic web can be detected in projection using photometric redshifts in slices along the Line of Sight, which enable the exploration of larger cosmic volumes. However, this comes at the expense of a lower redshift precision. It is therefore crucial to assess the differences between filaments extracted from exact redshifts and from photometric redshifts for a specific survey. We apply this analysis to capture the uncertainties and biases of filament extractions introduced by using the photometric sample of the Euclid Wide Survey. The question that we address in this work is how can we compare two filament samples derived with redshifts of different precisions in the Euclid Wide Survey context. We apply the cosmic web detection algorithm DisPerSE, in the redshift range $0.1 \leq z \leq 0.5$, to the GAlaxy Evolution and Assembly (GAEA) simulated galaxy sample which reproduces several characteristics of the Euclid Wide Survey. We develop a method to compare skeletons derived from photometric redshifts to those derived from true galaxy positions. This method expands the commonly used measure of distance between filaments to include geometrical (angles between filaments) and astrophysical considerations (galaxy mass gradients and connectivity-mass relations). We assess whether this approach strengthens our ability to correctly identify filaments in very large surveys such as the Euclid Wide Survey. [abridged]

astro-ph.CO↗