Euclid preparation
Astronomy & Astrophysics EDP Sciences 700 (2025) a78
Abstract:
The two-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission is aimed at performing an extensive spectroscopic survey of approximately 20–30 million H α -emitting galaxies up to a redshift of about 2. This ambitious project seeks to elucidate the nature of dark energy by mapping the three-dimensional clustering of galaxies over a significant portion of the sky. This paper presents the methodology and software developed for estimating the three-dimensional two-point correlation function within the Euclid Science Ground Segment. The software is designed to overcome the significant challenges posed by the large and complex Euclid dataset, which involves millions of galaxies. The key challenges include efficient pair counting, managing computational resources, and ensuring the accuracy of the correlation function estimation. The software leverages advanced algorithms, including k -d tree, octree, and linked-list data partitioning strategies, to optimise the pair-counting process. These methods are crucial for handling the massive volume of data efficiently. The implementation also includes parallel processing capabilities using shared-memory open multi-processing to further enhance performance and reduce computation times. Extensive validation and performance testing of the software are presented. Those have been performed by using various mock galaxy catalogues to ensure that it meets the stringent accuracy requirement of the Euclid mission. The results indicate that the software is robust and can reliably estimate the two-point correlation function, which is essential for deriving cosmological parameters with high precision. Furthermore, the paper discusses the expected performance of the software during different stages of Euclid Wide Survey observations and forecasts how the precision of the correlation function measurements will improve over the mission’s timeline, highlighting the software’s capability to handle large datasets efficiently.Euclid preparation
Astronomy & Astrophysics EDP Sciences 698 (2025) ARTN A233
Abstract:
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 cold dark matter (ΛCDM): 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<inf>10</inf>| f<inf>R</inf><inf>0</inf>|, is found to be 0.5σ when FORGE is used to create the synthetic data with log<inf>10</inf>| f<inf>R</inf><inf>0</inf>| = −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 baryonic parameters are well constrained despite the degeneracies among these parameters. However, the difference in the nonlinear dark matter prediction can be compensated for the adjustment of baryonic parameters, and the one-dimensional marginalised constraint on log<inf>10</inf>| f<inf>R</inf><inf>0</inf>| is biased. This bias can be avoided in the pessimistic setting at the expense of weaker constraints. For the pessimistic setting, using the ΛCDM synthetic data for WL, we obtain the prior-independent upper limit of log<inf>10</inf>| f<inf>R</inf><inf>0</inf>| < −5.6. Finally, we implement a method to include theoretical errors to avoid the bias due to inaccuracies in the nonlinear matter power spectrum prediction.Euclid: Early Release Observations The intracluster light of Abell 2390
Astronomy and Astrophysics 698 (2025)
Abstract:
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 (YEuclid preparation
Astronomy & Astrophysics EDP Sciences 698 (2025) ARTN A14
Abstract:
The intracluster light (ICL) permeating galaxy clusters is a tracer of the cluster assembly history and potentially a tracer of their dark matter structure. In this work, we explore the capability of the Euclid Wide Survey to detect ICL using HE-band mock images. We simulated clusters across a range of redshifts (0.3-1.8) and halo masses (1013:9-1015:0 M_) using an observationally motivated model of ICL. We identified a 50- 200 kpc circular annulus around the brightest cluster galaxy (BCG) in which the signal-to-noise ratio of the ICL is maximised and used the S/N within this aperture as our figure of merit for ICL detection.We compared three state-of-the-art methods for ICL detection and found that a method that performs simple aperture photometry after high-surface brightness source masking is able to detect ICL with minimal bias for clusters more massive than 1014:2 M_. The S/N of the ICL detection is primarily limited by the redshift of the cluster, which is driven by cosmological dimming rather than the mass of the cluster. Assuming the ICL in each cluster contains 15% of the stellar light, we forecast that Euclid will be able to measure the presence of ICL in up to _80 000 clusters of >1014:2 M_ between z = 0:3 and 1.5 with an S/N > 3. Half of these clusters will reside below z = 0:75, and the majority of those below z = 0:6 will be detected with an S/N > 20. A few thousand clusters at 1:3 < z < 1:5 will have ICL detectable with an S/N > 3. The surface brightness profile of the ICL model is strongly dependent on both the mass of the cluster and the redshift at which it is observed so that the outer ICL is best observed in the most massive clusters of >1014:7 M_. Euclid will detect the ICL at a distance of more than 500 kpc from the BCG, up to z = 0:7, in several hundred of these massive clusters over its large survey volume.Euclid: Early Release Observations – Overview of the Perseus cluster and analysis of its luminosity and stellar mass functions
Astronomy and Astrophysics 697 (2025)