arXiv subjects

V. F. Cardone

Publications and source records attributed to V. F. Cardone.

At least 19 recordsLinked to original sources

arXiv2026

Euclid preparation. The shape of halo profiles in $\Lambda$CDM and non-standard cosmologies

We study the shape of three-dimensional and projected dark-matter halo profiles extracted from cosmological $N$-body simulations in $\Lambda$CDM and non-standard cosmologies, using the \texttt{DUSTGRAIN-PF} and \texttt{DEMNUni} suites. The models considered include massive neutrinos, $f(\mathcal{R})$ gravity, and dynamical dark energy. By comparing density, mass, velocity-dispersion, and excess-surface-density profiles up to $5\,r_{500{\rm c}}$, we quantify the differential imprint of non-standard physics on halo structure in view of \textit{Euclid} cluster WL studies. Our main analysis is performed at $z=1.1$, a high-redshift regime where the weak-lensing signal-to-noise starts to degrade, providing a conservative stress test for detectability; for \texttt{DUSTGRAIN-PF} we additionally analyse $z=0.5$ and $z=0.3$ snapshots. In low-mass haloes ($M_{\rm 200c}<7\times10^{13}\,M_\odot$), $f(\mathcal{R})$ gravity produces deviations of order $10\,\%$ in projected and three-dimensional profiles, especially in the outskirts where screening is less efficient. Massive neutrinos partially reduce this signal, reflecting the competition between free streaming and fifth-force-enhanced growth. Dynamical dark energy and massive-neutrino cosmologies generally induce smaller, few-percent deviations, with the largest effects again found in low-mass haloes and at large radii. Under simplified assumptions for \Euclid WL, detecting such profile differences at $z=1.1$ requires stacks of $\sim10^5$ haloes, while a few thousands haloes may be sufficient at $z\lesssim0.5$. This further calls for the need of integrating such precise modelling of non-standard effects -- along with other observational effects -- in any likelihood involving \textit{Euclid} WL masses to avoid non-negligible systematic biases. Concentration--mass relations show weaker cosmology dependence, typically at the $\sim5\,\%$ level. [...]

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arXiv2026

Euclid: Inferring star-formation history via cross-correlations of photometric clustering and shear with the cosmic infrared background

The cosmic infrared background, sourced by dust heated by star-forming activity, encodes the integrated history of the star-formation distribution over a large swathe of cosmic time. Decomposing the contribution from galaxies at different redshifts to the observed CIB maps provides a powerful tool for probing the large-scale star-formation history across cosmic times. To this end, we perform a forecast tomographic cross-correlation analysis using simulated photometric galaxy clustering and weak lensing data based on the Euclid mission survey specifications, combined with Planck CIB observations. The analysis adopts templates constructed from the halo occupation distribution model to measure the bias-weighted star-formation-rate density, $\langle b \rho_{\rm SFRD}\rangle$, as a function of redshift. We present forecasts for the $\langle b \rho_{\rm SFRD}\rangle$ constraints based on these simulations and quantify the expected constraining power using Fisher information matrix methods. Compared with results obtained using the same dataset as in previous works, we find that Euclid will tighten the constraints on $\langle b \rho_{\rm SFRD}\rangle$ across all redshift bins by a factor of about $2$ and provide more measurements over a deeper redshift range. This leads to improved constraints on all HOD parameters, typically reducing the marginalized uncertainties by a factor of about $2.5$, while also breaking parameter degeneracies.

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arXiv2026

Euclid: Calibrating distances from surface brightness fluctuations with Early Release Observations of the Fornax cluster

Surface brightness fluctuations (SBF), the pixel-to-pixel variations in flux that arise from the statistical distribution of stars in galaxy images, provide a powerful tool to measure redshift-independent distances from photometric data alone. This method is particularly important in the era of large imaging surveys, such as those carried out during the Euclid mission. Here we present the first application of SBF to Euclid data, using the FAST-SBF code to measure stellar fluctuation amplitudes in the $I_\mathrm{E}$ band for a sample of galaxies in the Early Release Observations (ERO) of the Fornax galaxy cluster. Although the Euclid data reduction pipeline is not optimized for SBF measurements, extensive testing suggests that we are able to extract robust results. We calibrate the absolute fluctuation magnitude $\overline{M}_\mathrm{IE}$ as a function of the $(I_\mathrm{E}{-}H_\mathrm{E})$ colour for 15 galaxies in Fornax, then test this relation on galaxies in two other ERO fields: the Perseus cluster and dwarf satellite candidates around NGC 6744. Overall, we find reasonable agreement with distances in the literature and good agreement in cases where FAST-SBF indicates the measurements are robust. Finally, we compare our results against Stellar Population Tools (SPoT) simple stellar population models, and discuss the possibility of using SBF with Euclid to probe the underlying stellar populations of the galaxies.

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arXiv2026

Euclid: Measuring the intrinsic alignment of galaxies around cosmic voids in the \Euclid Flagship simulation\

We present a methodology to measure the intrinsic alignment (IA) signal of galaxies in the vicinity of cosmic voids using the \Euclid-like Flagship cosmological simulation from the Euclid Consortium. The IA signal is quantified and compared with the predictions of the linear alignment (LA) model, providing one of the first detailed investigations of this effect in underdense large-scale environments. While the IA signal around cosmic voids has received little attention to date, it may constitute a non-negligible systematic in forthcoming cosmological analyses that exploit void-lensing measurements. Our analysis examines red and blue galaxy populations separately, enabling a comparison of their alignment behaviour in void environments with the corresponding trends measured in galaxy-galaxy correlations. We find that the redshift evolution of the IA amplitude in cosmic voids is broadly consistent with that measured in the general galaxy population for both colour-selected samples. Additionally, our modelling allows us to estimate the linear bias of voids, $b_{\rm V}(z)$ which characterises how cosmic voids trace the underlying dark-matter density field, for voids with radii in the range $10 < R_{\rm V}/(h^{-1} {\rm Mpc}) < 15$. The measured bias exhibits a positive trend with redshift, consistent with theoretical predictions for the clustering of underdense regions. These results highlight the importance of accurately modelling IA in void studies, both to mitigate systematic effects in void-lensing cosmology and to further improve our understanding of galaxy-environment interactions in low-density regions of the Universe.

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arXiv2026

The PAU Survey and Euclid: Analysing photometric redshifts from realistically simulated narrow-band photometry with Flagship 2

The study of the large-scale structure of the Universe and the distribution of galaxies has been greatly advanced by the application of various types of photometric redshift estimation techniques. The Physics of the Accelerating Universe Survey (PAUS) is a state-of-the-art imaging survey, designed to provide high-quality photometric data in 40 optical narrow-band filters. In this paper, we present an in-depth analysis of the photometric redshifts obtained from PAUS using realistic simulations. Based on the Euclid Flagship 2 catalogue, we generate PAUS-like simulations with realistic photometric noise and target selection. The mock catalogue is used to explore the accuracy and precision of photometric redshifts of PAUS, investigating the impact of noise and depth, and combinations of broad- and narrow-band data. The simulations reproduce the observed PAUS performance well, with a robust photometric redshift scatter of $\sigma_{NMAD}/(1+z)\!=\!0.011$ for a mock subsample resembling the spectroscopic validation sample of the data. For the complete PAUS-like sample, which can only be evaluated in the simulation, we find $\sigma_{NMAD}/(1+z)\!=\!0.028$ for $i_{\rm AB}\!\lesssim\!23$ and outlier fractions below 10%. Forecasts indicate that including Euclid photometry in a joint analysis could further reduce scatter and outlier fractions, especially for faint galaxy populations. The hypothetical case of deeper PAUS observations over a limited sky area, forecasting the potential for future narrow- or medium-band surveys, in combination with Euclid's deep photometry, achieves scatter as low as $\sigma_{NMAD}/(1+z)\!=\!0.011$ and outlier fractions below 4% for $i_{\rm AB}\!<\!23.5$.

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arXiv2026

Euclid Quick Data Release (Q2) -- The Euclid Galactic Bulge Survey

The Euclid Quick Data Release Q2 provides an unprecedented deep, wide-field, high-angular-resolution view of the inner Galactic bulge through the Euclid Galactic Bulge Survey (EGBS). Nine contiguous fields covering 4.8 deg$^2$ were observed with the VIS instrument over 24 hours in March 2025. Unlike the nominal Euclid survey strategy, the EGBS employed 16 dithered exposures of 400 s each, corresponding to a total integration time of 1.8 hours per field. Dedicated calibration observations were obtained to derive point spread functions (PSFs). The primary objective of the EGBS is gravitational microlensing, with high-angular-resolution imaging enabling lens-mass measurements to better than 10%. The survey provides an optical reference dataset for previously discovered microlensing events and future observations of the Galactic bulge. The Q2 data were processed with the VIS-PF pipeline. The non-standard observing strategy required dedicated calibration products, while the extreme stellar density necessitated modifications to the astrometric calibration and cosmic-ray detection procedures. These improvements have since been incorporated into later pipeline versions. We describe the motivation, observing strategy, data processing, products, and first results of the EGBS. Astrometric residuals with respect to the Gaia DR3 catalogue are 5.5 mas in right ascension and 4.4 mas in declination across the survey area, while the photometric zero points are calibrated to 1.5%. The Q2 release includes calibrated single-dither images, dedicated PSF models, and photometric catalogues containing approximately 45 million detected sources per dither down to AB magnitude 26. Although incomplete because of extreme crowding, these products provide a robust astrometric and photometric foundation for future exploitation of the dataset.

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arXiv2026

Euclid preparation. First investigation of the impact of cross-contamination on spectroscopic redshift measurements with pixel-level simulations

We present a study on simulated data focused on understanding the performance of the spectroscopic redshift measurements with the Near-Infrared Spectrometer and Photometer (NISP) instrument on Euclid. Simulations include scenarios with different levels of cross-contamination arising from overlapping spectra of nearby sources, which represents one of the main drawbacks of slitless spectroscopy. We present a new analysis based on pixel-level simulations of the NISP images, with the data processed using the Euclid spectroscopic pipeline. We first consider an idealised case with non-overlapping spectra to assess the accuracy and reliability of the redshift measurement as a function of the flux of the H-alpha emission line and galaxy size. We then introduce more realistic contamination scenarios, distinguishing between two contributions: contamination from H-alpha emitters, which are the Euclid targets for cosmological analyses, and contamination from all other galaxies. In the second case, we analyse the impact of cross-contamination with an increasing number of contaminants, from the brighter to the fainter galaxies. Given that our results show no clear evidence that sources fainter than magnitude 20 degrade redshift measurements, we conservatively restrict our analysis to galaxies with magnitudes up to 24. In particular, we provide a preliminary estimate that contamination from galaxies within the same redshift range as the target sample contributes to about 4% of the total degradation due to cross-contamination from all galaxies.

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arXiv2026

Euclid: Quick Data Release (Q1) -- LensMC shear measurement catalogue for cluster lensing science

We present a LensMC lensing analysis of Euclid Quick Release 1 images that were made available in March 2025. We measured shapes, positions, weights, and other morphological parameters of galaxies with a surface number density of $26\;\text{arcmin}^{-2}$ for $I_{\scriptscriptstyle\rm E}<24.5$, achieving 75 arcmin$^{-2}$ for $I_{\scriptscriptstyle\rm E}<27$, in 63 deg$^2$ of Euclid VIS images. This is the first shear measurement catalogue produced with \lensmc in anticipation of the Euclid Data Release 1. To within the scope of this work and availability of survey volume, we found no spatial dependency in the additive biases. However, we developed an empirical bias correction based jointly on galaxy sizes and magnitudes, which was applied to the measurement of the lensing signal over the whole area. In order to validate the quality of our measurements, we calculated two-point statistics and cluster profile measurements, and cross-checked results with external cluster catalogues from WISE and the Dark Energy Survey. Additionally, by stacking shear profiles of random clusters we found that the low-redshift, large radii bins may be still contaminated by residual systematic effects. Thanks to Euclid image resolution and depth and overall good control of systematic errors, we are able to constrain the lensing profiles of clusters with masses of $10^{14}M_\odot$ out to $z\approx2$ over nearly 10 Gyr of evolution history.

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arXiv2026

Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations

The evolution of galaxies is profoundly influenced by the environment in which they reside. Cosmic voids serve as pristine laboratories for studying galaxy evolution in the relative absence of the complex physical processes that dominate denser environments. In this study, we investigate galaxy properties and merger histories as a function of environment using the GAlaxy Evolution and Assembly (GAEA) mock-observation lightcone replicating the Euclid Deep Survey as foreseen for the first Euclid data release. The H$\alpha$-selected galaxy sample spans the redshift range $0.4 < z < 1.8$, corresponding to the interval over which H$\alpha$ is accessible to Euclid slitless spectroscopy. We classify galaxies based on their void-centric distance and local density contrast, and compare their stellar mass, specific star formation rate, bulge-to-total stellar mass ratio, and halo mass across different environments. We further analyse the merger histories of these galaxies to study their assembly evolution. We find that galaxies located closer to void centres ($d_{\rm cc} \lesssim 0.7 R_{\rm v}$) are less massive, more actively star-forming, and more disc-dominated than galaxies in denser regions. Merger histories indicate that void galaxies do not experience fewer mergers, but rather that mergers occur later relative to galaxies in high-density regions. These results support a scenario in which the environment regulates the timing and nature of mergers rather than their overall frequency, producing a slower evolutionary path in low-density regions. We conclude by discussing the extent to which these trends are shaped by environmental parametrisation methods and observational selection effects. Our analysis provides a framework for interpreting forthcoming Euclid data and demonstrates Euclid's potential to identify cosmic voids and probe environmental effects on galaxy evolution.

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arXiv2026

Euclid preparation. Three-dimensional galaxy clustering in configuration space: Three-point correlation function estimation

Higher-order correlation functions are firmly established as a fundamental tool for the statistical analysis of clustering in modern galaxy surveys. It was demonstrated that they greatly enrich the information content extracted by two-point statistics, allowing us to break the degeneracies between model parameters and constrain departures from Gaussianity. This paper presents the statistical estimators adopted to evaluate the galaxy three-point correlation function and its numerical implementation within the data analysis pipeline of the Euclid Science Ground Segment. Two different algorithms are adopted to count triplets: a direct and exact counting method capable of providing a robust three-point correlation function measurement for any triangular configuration, and a more efficient method based on spherical harmonic decomposition, designed to address the computational challenges of measuring the three-point statistics for data sets as large as those of the final Euclid survey. The spherical harmonic decomposition estimates the Legendre coefficients of the three-point correlation function up to a finite expansion order. Despite being an approximation, the three-point function measured with this approach satisfies the scientific requirements of the mission. We also introduce, implement, and validate the random split technique, which reduces the computational cost of counting triplets in the reference random sample by a factor of 10, without significantly compromising numerical accuracy. We evaluated the robustness, precision, and accuracy of the numerical estimates through an extensive campaign of validation tests, the results of which are presented. Finally, we quantify the computational requirements and their scaling with the expected size of Euclid data set, showing that a complete three-point analysis of the final Euclid survey is within computational reach.

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arXiv2026

Euclid preparation. Refining input galaxy shape distributions for shear calibration simulations

The Euclid Wide Survey (EWS) will cover the majority of the extragalactic sky with a resolution similar to the Hubble Space Telescope. This unprecedented data set will introduce a new era of precision cosmology. However, systematic effects need to be controlled better than ever. One of the sources of systematic uncertainties in weak gravitational lensing are biases introduced during the shear measurement. Determining these biases precisely allows the calibration of cosmological measurements to within Euclid's required accuracy. The simulations that are used to determine such biases, need to resemble the real observations. In this work, we aim to learn distributions of galaxy shape parameters from real Euclid data and use the new information to augment the morphological information in the Flagship galaxy mock catalogue. The morphology is extracted using single and double-S\'ersic model fits to the real data, for which we use SourceXtractor++. We train our pipeline on deep Euclid observations of a field with rich auxiliary data and then use it to simulate EWS-like data. In these simulations we compare the multiplicative bias between the morphology from the Flagship catalogue, the trained single-S\'ersic morphology, and the trained double-S\'ersic morphology. We find that the image simulations with the updated morphology result in a percent-level change in the multiplicative shear bias compared to the original morphology from Flagship. This bias exceeds Euclid's tight error budget by a factor of five and underlines the need for this work. Furthermore, we study the sensitivity of the multiplicative bias to key morphological parameters and show that our approach satisfies the requirements for the cosmology analysis with the first data release of Euclid.

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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, $f\sigma_8$. We tested the dispersion, Scoccimarro, and Taruya-Nishimichi-Saito models. We find that the dispersion model yields unbiased inferences on $f\sigma_8$ 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.

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arXiv2026

Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification

We present an end-to-end, iterative pipeline for efficient identification of strong galaxy--galaxy lensing systems, applied to the Euclid Q1 imaging data. Starting from VIS catalogues, we reject point sources, apply a magnitude cut (I$_E$ $\leq$ 24) on deflectors, and run a pixel-level artefact/noise filter to build 96 $\times$ 96 pix cutouts; VIS+NISP colour composites are constructed with a VIS-anchored luminance scheme that preserves VIS morphology and NISP colour contrast. A VIS-only seed classifier supplies clear positives and typical impostors, from which we curate a morphology-balanced negative set and augment scarce positives. Among the six CNNs studied initially, a modified VGG16 (GlobalAveragePooling + 256/128 dense layers with the last nine layers trainable) performs best; the training set grows from 27 seed lenses (augmented to 1809) plus 2000 negatives to a colour dataset of 30,686 images. After three rounds of iterative fine-tuning, human grading of the top 4000 candidates ranked by the final model yields 441 Grade A/B candidate lensing systems, including 311 overlapping with the existing Q1 strong-lens catalogue, and 130 additional A/B candidates (9 As and 121 Bs) not previously reported. Independently, the model recovers 740 out of 905 (81.8%) candidate Q1 lenses within its top 20,000 predictions, considering off-centred samples. Candidates span I$_E$ $\simeq$ 17--24 AB mag (median 21.3 AB mag) and are redder in Y$_E$--H$_E$ than the parent population, consistent with massive early-type deflectors. Each training iteration required a week for a small team, and the approach easily scales to future Euclid releases; future work will calibrate the selection function via lens injection, extend recall through uncertainty-aware active learning, explore multi-scale or attention-based neural networks with fast post-hoc vetters that incorporate lens models into the classification.

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arXiv2026

Euclid preparation. Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing

One of the $\textit{Euclid}$ mission's key projects is the so-called 3$\times$2pt analysis, that is, the combination of cosmic shear, photometric galaxy clustering, and galaxy-galaxy lensing. Although $\textit{Euclid}$ has established quality requirements for the photo-$z$ accuracy needed for the weak lensing galaxy sample, no such requirements have been set for the photometric clustering sample. In this paper, we investigate the impact of redshift uncertainties on $\textit{Euclid}$'s photometric galaxy clustering analysis and its combination with weak gravitational lensing, focusing on data release 1 (DR1). In particular, we study whether having precise knowledge of the mean of the redshift distributions per bin is sufficient to avoid biases in the resulting cosmological constraints or whether accuracy in the higher-order moments of the distribution is required. We evaluate the results based on their constraining power on $w_{\mathrm{0}}$ and $w_{a}$ and define thresholds for the precision and accuracy of $\textit{Euclid}$'s redshift distribution of the photometric clustering sample. We find that the redshift distributions of the photometric clustering sample must be known at an accuracy of 0.004(1+$z$) in the mean in order to recover 80$\%$ of the constraining power in $\textit{Euclid}$'s DR1 $w_{\mathrm{0}}w_{a}$CDM 3$\times$2pt analysis. The impact of the uncertainty on the width is negligible, provided the mean redshift is constrained with sufficient accuracy. For most sources of redshift distribution error, attaining the requirement on the mean will also reduce uncertainty in the width well below the required level.

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arXiv2026

Euclid preparation. CII. Non-Gaussianity of 2-pt statistics likelihood: Parameter inference with a non-Gaussian likelihood in Fourier and configuration space

In this work we account for this skewness in parameter inference by modelling the likelihood through an Edgeworth expansion which involves the complete skewness tensor, composed of 1-point, 2-point, and 3-point correlators. To simplify the calculations of this expansion we perform a change of basis which reduces the precision matrix to the identity. In this basis, the off-diagonal elements of the skewness tensor are consistent with zero, while the amplitude of its diagonal match the level expected for a Gaussian underlying field. We perform parameter inference with this likelihood model and find that including only the diagonal part of the skewness is sufficient, while incorporating the full skewness tensor injects noise without improving accuracy. Despite the estimated excess skewness in the original basis, the cosmological constraints remain effectively unchanged when adopting a Gaussian likelihood or considering the more complete Edgeworth expansion, with variations in the figure of merit of cosmological parameters between the two cases below $5\%$. This result remains unchanged against variations of the survey volume and geometry, scale-cut, and 2-point statistic (power spectrum or correlation function). Using $10\, 000$ cloned \Euclid large mocks based on realistic galaxy catalogues with characteristics close to future \Euclid data, we find no detectable excess skewness on intermediate scales, due to the level of shot noise expected for the \Euclid spectroscopic sample. We conclude that the Gaussian likelihood assumption is robust for \Euclid 2-point statistics analyses in both Fourier and configuration space.

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arXiv2026

Euclid preparation. Galaxy power spectrum and bispectrum modelling

Higher-order correlation functions of the large-scale galaxy distribution offer access to information beyond that contained in standard 2-point statistics such as the power spectrum. In this work we assess this potential for the $\textit{Euclid}$ mission using synthetic catalogues of H$\alpha$ galaxies based on the 54 $\, h^{-3} \, {\rm Gpc}^3$ Flagship I simulation, designed to reproduce the $\textit{Euclid}$ spectroscopic sample. We comprehensively validate the one-loop galaxy power spectrum and tree-level bispectrum predictions from perturbation theory in both real and redshift space. Assuming scale cuts consistent with our previous power spectrum study on the same catalogues, this modelling yields unbiased cosmological constraints for the bispectrum up to $k_{\rm max} = 0.15\,\, h \, {\rm Mpc}^{-1}$ in real space and $0.08 \, (0.1)\,\, h \, {\rm Mpc}^{-1}$ at the lowest (highest) redshift, corresponding to $z=0.9$ ($z=1.8$), for the monopole and quadrupole in redshift space using statistical uncertainties corresponding to the full simulation volume. With these scale cuts, adding bispectrum information to the power spectrum improves constraints on the amplitude of scalar perturbations and the matter density by up to 30 %, increasing the overall figure of merit for key cosmological parameters by a factor of about 2.5. Similar conclusions hold when statistical uncertainties are rescaled to a $\textit{Euclid}$-like volume, highlighting the importance of the bispectrum for fully exploiting the forthcoming $\textit{Euclid}$ data. Our analysis also provides the first detailed characterisation of the nonlinear bias model of H$\alpha$ emitters, showing that bias relations calibrated on low-resolution \textit{N}-body simulations do not adequately describe the clustering of H$\alpha$ galaxies at low redshift, whereas excursion-set and co-evolution relations for tidal biases remain accurate.

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arXiv2026

Euclid preparation. Cosmology Likelihood for Observables in Euclid (CLOE). 2. Code implementation

We provide a description of the code implementation and structure of Cosmology Likelihood for Observables in Euclid (CLOE), developed by members of the Euclid Consortium. CLOE is a modular Python code for computing the theoretical predictions of cosmological observables and evaluating them against state-of-the-art data from galaxy surveys such as Euclid in a unified likelihood. This primarily includes the core observables of weak gravitational lensing, photometric galaxy clustering, galaxy-galaxy lensing, and spectroscopic galaxy clustering, but also extended probes such as the clusters of galaxies and cross-correlations of galaxy positions and shapes with the cosmic microwave background. While CLOE has been developed to serve as the unified framework for the parameter inferences in Euclid, it has general capabilities that can serve the broader cosmological community. It is different from other comparable cosmological tools in that it is written entirely in Python, performs the full likelihood calculation, and includes both photometric and spectroscopic observables. We will focus on the primary probes of Euclid and will describe the overall code structure, rigorous code development practices, extensive documentation, unique features, speed optimization, and future development plans. CLOE is publicly available at https://github.com/cloe-org/cloe.

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arXiv2026

Euclid preparation. Simulated galaxy catalogues for non-standard cosmological models

Stage-IV galaxy surveys will provide the opportunity to test cosmological models and the underlying theory of gravity with unparalleled precision. In this context, it is crucial for the Euclid mission to leverage its spectroscopic and photometric probes to systematically investigate and incorporate non-standard cosmological models, including modified gravity, alternative dark energy scenarios, massive neutrinos, and primordial non-Gaussianity. We produce and release publicly simulated galaxy catalogues from a broad suite of non-standard cosmological simulations, which we processed through a model-independent analytical pipeline, making use of Rockstar for halo identification, and a modified version of the SciPic library for the galaxy-halo connection using the halo occupation distribution framework. We investigate their galaxy-clustering characteristics via the multipoles of the 2PCF in redshift space and VDG, a highly performant model for galaxy clustering. Across a wide range of models, the linear growth rate multiplied by the matter density within spheres of radius 12,Mpc, fs12, exhibits a notable robustness to the choice of cosmological template. Compared to previous works, our study extends this result to numerous scenarios with markedly distinct gravitational or dark energy dynamics. We find that the most of the scatter in cosmological parameter inference already appears when using the cosmological model of the simulations as templates. Using a `wrong' template can also introduce an additional scatter, although with smaller amplitude. Often, we find deviations much larger than error bars, meaning that the Gaussian approximation for the covariance might need to be further studied. Future cosmological investigations must broaden their scope to include a diverse array of non-standard theoretical frameworks, extending beyond LCDM and rudimentary dynamic dark energy models.

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