arXiv subjects

A. Pourtsidou

Publications and source records attributed to A. Pourtsidou.

At least 19 recordsLinked to original sources

arXiv2026

Euclid preparation. XCVI. Cosmology Likelihood for Observables in Euclid (CLOE). 3. Inference and Forecasts

The Euclid mission aims to measure the positions, shapes, and redshifts of over a billion galaxies to provide unprecedented constraints on the nature of dark matter and dark energy. Achieving this goal requires a continuous reassessment of the mission's scientific performance, particularly in terms of its ability to constrain cosmological parameters, as our understanding of how to model large-scale structure observables improves. In this study, we present the first scientific forecasts using CLOE (Cosmology Likelihood for Observables in Euclid), a dedicated Euclid cosmological pipeline developed to support this endeavour. Using advanced Bayesian inference techniques applied to synthetic Euclid-like data, we sample the posterior distribution of cosmological and nuisance parameters across a variety of cosmological models and Euclid primary probes: cosmic shear, angular photometric galaxy clustering, galaxy-galaxy lensing, and spectroscopic galaxy clustering. We validate the capability of CLOE to produce reliable cosmological forecasts, showcasing Euclid's potential to achieve a figure of merit for the dark energy parameters $w_0$ and $w_a$ exceeding 400 when combining all primary probes. Furthermore, we illustrate the behaviour of the posterior probability distribution of the parameters of interest given different priors and scale cuts. Finally, we emphasise the importance of addressing computational challenges, proposing further exploration of innovative data science techniques to efficiently navigate the Euclid high-dimensional parameter space in upcoming cosmological data releases.

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arXiv2026

Dark Energy Survey Year 6 Results: Weak Lensing and Galaxy Clustering Cosmological Analysis Framework

We present the methodology for the weak lensing and galaxy clustering analyses of the Dark Energy Survey (DES) Year 6 data set. In this work, we design and validate the analysis pipeline for the cosmic shear, galaxy clustering plus galaxy$-$galaxy lensing ($2 \times 2$pt), and the joint analysis in the $3 \times 2$pt. Our framework accounts for key theoretical uncertainties, such as baryonic feedback and galaxy bias, incorporating both linear and non-linear models. We apply scale cuts in regimes where theoretical modeling becomes unreliable. The robustness of the pipeline is validated using mock data and simulations, confirming unbiased cosmological constraints and highlighting the importance of posterior projection effects in the validation process. As a result, we deliver robust and validated analysis pipelines for cosmic shear, $2 \times 2$pt, and $3 \times 2$pt in $\Lambda$CDM and $w$CDM scenarios, including a well-defined set of scales suitable for real data analysis, a robust prescription for theoretical systematics, and the theoretical covariance of the signal. This comprehensive methodology also lays the groundwork for future galaxy surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time.

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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.

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arXiv2025

Interacting dark energy constraints from the full-shape analyses of BOSS DR12 and DES Year 3 measurements

Dark Scattering (DS) is an interacting dark energy model characterised by pure momentum exchange between dark energy and dark matter. It is phenomenologically interesting because it is unconstrained by CMB data and can alleviate the $S_8$ tension. We derive constraints on cosmological and DS parameters using three two-point correlation functions (3$\times$2pt) from the Dark Energy Survey third year data release (DES Y3). We then add information from the multipoles of the galaxy power spectrum combined with Baryonic Acoustic Oscillation (BAO) measurements using the twelfth data release of the Baryon Oscillation Spectroscopic Survey (BOSS DR12) and external BAO measurements. We compare results from the direct combination of the probes with the joint posterior distribution calculated with a normalising flow approach. Additionally, we run a CMB analysis with the Planck Public Release 4 (PR4) for comparison of the cosmological constraints. Overall, we find that the combination of probes allows minimising the projection effects and improves constraints without the need to include CMB information. It brings the marginalised posterior maxima closer to the corresponding best-fit values and weakens the sensitivity to the priors of the spectroscopic modelling nuisance parameters. These findings are highly relevant in light of forthcoming data of surveys like DESI, Euclid, and Rubin.

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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.

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arXiv2025

Euclid preparation LXIII. Simulations and nonlinearities beyond $Λ$CDM. 2. Results from non-standard simulations

The Euclid mission will measure cosmological parameters with unprecedented precision. To distinguish between cosmological models, it is essential to generate realistic mock observables from cosmological simulations that were run in both the standard $Λ$-cold-dark-matter ($Λ$CDM) paradigm and in many non-standard models beyond $Λ$CDM. We present the scientific results from a suite of cosmological N-body simulations using non-standard models including dynamical dark energy, k-essence, interacting dark energy, modified gravity, massive neutrinos, and primordial non-Gaussianities. We investigate how these models affect the large-scale-structure formation and evolution in addition to providing synthetic observables that can be used to test and constrain these models with Euclid data. We developed a custom pipeline based on the Rockstar halo finder and the nbodykit large-scale structure toolkit to analyse the particle output of non-standard simulations and generate mock observables such as halo and void catalogues, mass density fields, and power spectra in a consistent way. We compare these observables with those from the standard $Λ$CDM model and quantify the deviations. We find that non-standard cosmological models can leave significant imprints on the synthetic observables that we have generated. Our results demonstrate that non-standard cosmological N-body simulations provide valuable insights into the physics of dark energy and dark matter, which is essential to maximising the scientific return of Euclid.

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arXiv2024

Classifying Modified Gravity and Dark Energy Theories with Bayesian Neural Networks: Massive Neutrinos, Baryonic Feedback, and the Theoretical Error

We study the capacity of Bayesian Neural Networks (BNNs) to detect new physics in the dark matter power spectrum. As in previous studies, the Bayesian Cosmological Network (BaCoN) classifies spectra into one of 5 classes: $Λ$CDM, $f(R)$, $w$CDM, Dvali-Gabadaze-Porrati (DGP) gravity and a 'random' class, with this work extending it to include the effects of massive neutrinos and baryonic feedback. We further develop the treatment of theoretical errors in BaCoN-II, investigating several approaches and identifying the one that best allows the trained network to generalise to other power spectrum modelling prescriptions. In particular, we compare power spectra data produced by EuclidEmulator2, HMcode and halofit, all supplemented with the halo model reaction to model beyond-$Λ$CDM physics. We investigate BNN-classifiers trained on these sets of spectra, adding in Stage-IV survey noise and various theoretical error models. Using our optimal theoretical error model, our fiducial classifier achieves a total classification accuracy of $\sim$ 95% when it is trained on EuclidEmulator2-based spectra with modification parameters drawn from a Gaussian distribution centred around $Λ$CDM ($f(R)$: $σ_{fR0} = 10^{-5.5}$, DGP: $σ_{r\mathrm{c}} = 0.173$, $w$CDM: $σ_{w0} = 0.097$, $σ_{wa}=0.32$). This strengthens the promise of this method to glean the maximal amount of unbiased gravitational and cosmological information from forthcoming Stage-IV galaxy surveys.

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arXiv2024

Euclid preparation. Simulations and nonlinearities beyond $Λ$CDM. 1. Numerical methods and validation

To constrain models beyond $Λ$CDM, the development of the Euclid analysis pipeline requires simulations that capture the nonlinear phenomenology of such models. We present an overview of numerical methods and $N$-body simulation codes developed to study the nonlinear regime of structure formation in alternative dark energy and modified gravity theories. We review a variety of numerical techniques and approximations employed in cosmological $N$-body simulations to model the complex phenomenology of scenarios beyond $Λ$CDM. This includes discussions on solving nonlinear field equations, accounting for fifth forces, and implementing screening mechanisms. Furthermore, we conduct a code comparison exercise to assess the reliability and convergence of different simulation codes across a range of models. Our analysis demonstrates a high degree of agreement among the outputs of different simulation codes, providing confidence in current numerical methods for modelling cosmic structure formation beyond $Λ$CDM. We highlight recent advances made in simulating the nonlinear scales of structure formation, which are essential for leveraging the full scientific potential of the forthcoming observational data from the Euclid mission.

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arXiv2024

Euclid preparation. Modelling spectroscopic clustering on mildly nonlinear scales in beyond-$Λ$CDM models

We investigate the approximations needed to efficiently predict the large-scale clustering of matter and dark matter halos in beyond-$Λ$CDM scenarios. We examine the normal branch of the Dvali-Gabadadze-Porrati model, the Hu-Sawicki $f(R)$ model, a slowly evolving dark energy, an interacting dark energy model and massive neutrinos. For each, we test approximations for the perturbative kernel calculations, including the omission of screening terms and the use of perturbative kernels based on the Einstein-de Sitter universe; we explore different infrared-resummation schemes, tracer bias models and a linear treatment of massive neutrinos; we employ two models for redshift space distortions, the Taruya-Nishimishi-Saito prescription and the Effective Field Theory of Large-Scale Structure. This work further provides a preliminary validation of the codes being considered by Euclid for the spectroscopic clustering probe in beyond-$Λ$CDM scenarios. We calculate and compare the $χ^2$ statistic to assess the different modelling choices. This is done by fitting the spectroscopic clustering predictions to measurements from numerical simulations and perturbation theory-based mock data. We compare the behaviour of this statistic in the beyond-$Λ$CDM cases, as a function of the maximum scale included in the fit, to the baseline $Λ$CDM case. We find that the Einstein-de Sitter approximation without screening is surprisingly accurate for all cases when comparing to the halo clustering monopole and quadrupole obtained from simulations. Our results suggest that the inclusion of multiple redshift bins, higher-order multipoles, higher-order clustering statistics (such as the bispectrum) and photometric probes such as weak lensing, will be essential to extract information on massive neutrinos, modified gravity and dark energy.

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arXiv2023

Euclid: Constraints on f(R) cosmologies from the spectroscopic and photometric primary probes

$\textit{Euclid}$ will provide a powerful compilation of data including spectroscopic redshifts, the angular clustering of galaxies, weak lensing cosmic shear, and the cross-correlation of these last two photometric observables. In this study we extend recently presented $\textit{Euclid}$ forecasts into the Hu-Sawicki $f(R)$ cosmological model, a popular extension of the Hilbert-Einstein action that introduces an universal modified gravity force in a scale-dependent way. Our aim is to estimate how well future $\textit{Euclid}$ data will be able to constrain the extra parameter of the theory, $f_{R0}$, for the range in which this parameter is still allowed by current observations. For the spectroscopic probe, we use a phenomenological approach for the scale dependence of the growth of perturbations in the terms related to baryon acoustic oscillations and redshift-space distortions. For the photometric observables, we use a fitting formula that captures the modifications in the non-linear matter power spectrum caused by the $f(R)$ model. We show that, in an optimistic setting, and for a fiducial value of $f_{R0} = 5 \times 10^{-6}$, $\textit{Euclid}$ alone will be able to constrain the additional parameter $\log f_{R0}$ at the $3\%$ level, using spectroscopic galaxy clustering alone; at the $1.4\%$ level, using the combination of photometric probes on their own; and at the $1\%$ level, using the combination of spectroscopic and photometric observations. This last constraint corresponds to an error of the order of $6 \times 10^{-7}$ at the $1σ$ level on the model parameter $f_{R0} = 5 \times 10^{-6}$. We report also forecasted constraints for $f_{R0} = 5 \times 10^{-5}$ and $f_{R0} = 5 \times 10^{-7}$ and show that in the optimistic scenario, $\textit{Euclid}$ will be able to distinguish these models from $Λ\mathrm{CDM}$ at more than 3$σ$. (abridged)

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arXiv2023

Euclid: Forecasts from the void-lensing cross-correlation

The Euclid space telescope will survey a large dataset of cosmic voids traced by dense samples of galaxies. In this work we estimate its expected performance when exploiting angular photometric void clustering, galaxy weak lensing and their cross-correlation. To this aim, we implement a Fisher matrix approach tailored for voids from the Euclid photometric dataset and present the first forecasts on cosmological parameters that include the void-lensing correlation. We examine two different probe settings, pessimistic and optimistic, both for void clustering and galaxy lensing. We carry out forecast analyses in four model cosmologies, accounting for a varying total neutrino mass, $M_ν$, and a dynamical dark energy (DE) equation of state, $w(z)$, described by the CPL parametrisation. We find that void clustering constraints on $h$ and $Ω_b$ are competitive with galaxy lensing alone, while errors on $n_s$ decrease thanks to the orthogonality of the two probes in the 2D-projected parameter space. We also note that, as a whole, the inclusion of the void-lensing cross-correlation signal improves parameter constraints by $10-15\%$, and enhances the joint void clustering and galaxy lensing Figure of Merit (FoM) by $10\%$ and $25\%$, in the pessimistic and optimistic scenarios, respectively. Finally, when further combining with the spectroscopic galaxy clustering, assumed as an independent probe, we find that, in the most competitive case, the FoM increases by a factor of 4 with respect to the combination of weak lensing and spectroscopic galaxy clustering taken as independent probes. The forecasts presented in this work show that photometric void-clustering and its cross-correlation with galaxy lensing deserve to be exploited in the data analysis of the Euclid galaxy survey and promise to improve its constraining power, especially on $h$, $Ω_b$, the neutrino mass, and the DE evolution.

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arXiv2023

Fast and accurate predictions of the nonlinear matter power spectrum for general models of Dark Energy and Modified Gravity

We embed linear and nonlinear parametrisations of beyond standard cosmological physics in the halo model reaction framework, providing a model-independent prescription for the nonlinear matter power spectrum. As an application, we focus on Horndeski theories, using the Effective Field Theory of Dark Energy (EFTofDE) to parameterise linear and quasi-nonlinear perturbations. In the nonlinear regime we investigate both a nonlinear parameterised-post Friedmannian (nPPF) approach as well as a physically motivated and approximate phenomenological model based on the error function (Erf). We compare the parameterised approaches' predictions of the nonlinear matter power spectrum to the exact solutions, as well as state-of-the-art emulators, in an evolving dark energy scenario and two well studied modified gravity models, finding sub-percent agreement in the reaction using the Erf model at $z\leq1$ and $k\leq 5~h/{\rm Mpc}$. This suggests only an additional 3 free constants, above the background and linear theory parameters, are sufficient to model nonlinear, non-standard cosmology in the matter power spectrum at scales down to $k \leq 3h~/{\rm Mpc}$ within $2\%$ accuracy. We implement the parametrisations into ver.2.0 of the ReACT code.

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arXiv2022

KiDS-1000 Cosmology: machine learning -- accelerated constraints on Interacting Dark Energy with COSMOPOWER

We derive constraints on a coupled quintessence model with pure momentum exchange from the public $\sim$1000 deg$^2$ cosmic shear measurements from the Kilo-Degree Survey and the $\it{Planck}$ 2018 Cosmic Microwave Background data. We compare this model with $Λ$CDM and find similar $χ^2$ and log-evidence values. We accelerate parameter estimation by sourcing cosmological power spectra from the neural network emulator COSMOPOWER. We highlight the necessity of such emulator-based approaches to reduce the computational runtime of future similar analyses, particularly from Stage IV surveys. As an example, we present MCMC forecasts on the same coupled quintessence model for a $\it{Euclid}$-like survey, revealing degeneracies between the coupled quintessence parameters and the baryonic feedback and intrinsic alignment parameters, but also highlighting the large increase in constraining power Stage IV surveys will achieve. The contours are obtained in a few hours with COSMOPOWER, as opposed to the few months required with a Boltzmann code.

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arXiv2021

$Euclid$ preparation: XV. Forecasting cosmological constraints for the $Euclid$ and CMB joint analysis

The combination and cross-correlation of the upcoming $Euclid$ data with cosmic microwave background (CMB) measurements is a source of great expectation since it will provide the largest lever arm of epochs, ranging from recombination to structure formation across the entire past light cone. In this work, we present forecasts for the joint analysis of $Euclid$ and CMB data on the cosmological parameters of the standard cosmological model and some of its extensions. This work expands and complements the recently published forecasts based on $Euclid$-specific probes, namely galaxy clustering, weak lensing, and their cross-correlation. With some assumptions on the specifications of current and future CMB experiments, the predicted constraints are obtained from both a standard Fisher formalism and a posterior-fitting approach based on actual CMB data. Compared to a $Euclid$-only analysis, the addition of CMB data leads to a substantial impact on constraints for all cosmological parameters of the standard $Λ$-cold-dark-matter model, with improvements reaching up to a factor of ten. For the parameters of extended models, which include a redshift-dependent dark energy equation of state, non-zero curvature, and a phenomenological modification of gravity, improvements can be of the order of two to three, reaching higher than ten in some cases. The results highlight the crucial importance for cosmological constraints of the combination and cross-correlation of $Euclid$ probes with CMB data.

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arXiv2021

Euclid: Forecasts for $k$-cut $3 \times 2$ Point Statistics

Modelling uncertainties at small scales, i.e. high $k$ in the power spectrum $P(k)$, due to baryonic feedback, nonlinear structure growth and the fact that galaxies are biased tracers poses a significant obstacle to fully leverage the constraining power of the {\it Euclid} wide-field survey. $k$-cut cosmic shear has recently been proposed as a method to optimally remove sensitivity to these scales while preserving usable information. In this paper we generalise the $k$-cut cosmic shear formalism to $3 \times 2$ point statistics and estimate the loss of information for different $k$-cuts in a $3 \times 2$ point analysis of the {\it Euclid} data. Extending the Fisher matrix analysis of~\citet{blanchard2019euclid}, we assess the degradation in constraining power for different $k$-cuts. We work in the idealised case and assume the galaxy bias is linear, the covariance is Gaussian, while neglecting uncertainties due to photo-z errors and baryonic feedback. We find that taking a $k$-cut at $2.6 \ h \ {\rm Mpc} ^{-1}$ yields a dark energy Figure of Merit (FOM) of 1018. This is comparable to taking a weak lensing cut at $\ell = 5000$ and a galaxy clustering and galaxy-galaxy lensing cut at $\ell = 3000$ in a traditional $3 \times 2$ point analysis. We also find that the fraction of the observed galaxies used in the photometric clustering part of the analysis is one of the main drivers of the FOM. Removing $50 \% \ (90 \%)$ of the clustering galaxies decreases the FOM by $19 \% \ (62 \%)$. Given that the FOM depends so heavily on the fraction of galaxies used in the clustering analysis, extensive efforts should be made to handle the real-world systematics present when extending the analysis beyond the luminous red galaxy (LRG) sample.

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arXiv2021

Euclid preparation: XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses

The accuracy of photometric redshifts (photo-zs) particularly affects the results of the analyses of galaxy clustering with photometrically-selected galaxies (GCph) and weak lensing. In the next decade, space missions like Euclid will collect photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-zs. In this paper, we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from Euclid. We focus on GCph and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-z distributions based on the Euclid Consortium Flagship simulation and using a machine learning photo-z algorithm. We use the Fisher matrix formalism and these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-z accuracy. We find that bins with equal width in redshift provide a higher Figure of Merit (FoM) than equipopulated bins and that increasing the number of redshift bins from 10 to 13 improves the FoM by 35% and 15% for GCph and its combination with GGL, respectively. For GCph, an increase of the survey depth provides a higher FoM. But the addition of faint galaxies beyond the limit of the spectroscopic training data decreases the FoM due to the spurious photo-zs. When combining both probes, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. We conclude that there is more information that can be extracted beyond the nominal 10 tomographic redshift bins of Euclid and that we should be cautious when adding faint galaxies into our sample, since they can degrade the cosmological constraints.

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arXiv2020

Euclid preparation: VII. Forecast validation for Euclid cosmological probes

The Euclid space telescope will measure the shapes and redshifts of galaxies to reconstruct the expansion history of the Universe and the growth of cosmic structures. Estimation of the expected performance of the experiment, in terms of predicted constraints on cosmological parameters, has so far relied on different methodologies and numerical implementations, developed for different observational probes and for their combination. In this paper we present validated forecasts, that combine both theoretical and observational expertise for different cosmological probes. This is presented to provide the community with reliable numerical codes and methods for Euclid cosmological forecasts. We describe in detail the methodology adopted for Fisher matrix forecasts, applied to galaxy clustering, weak lensing and their combination. We estimate the required accuracy for Euclid forecasts and outline a methodology for their development. We then compare and improve different numerical implementations, reaching uncertainties on the errors of cosmological parameters that are less than the required precision in all cases. Furthermore, we provide details on the validated implementations that can be used by the reader to validate their own codes if required. We present new cosmological forecasts for Euclid. We find that results depend on the specific cosmological model and remaining freedom in each setup, i.e. flat or non-flat spatial cosmologies, or different cuts at nonlinear scales. The validated numerical implementations can now be reliably used for any setup. We present results for an optimistic and a pessimistic choice of such settings. We demonstrate that the impact of cross-correlations is particularly relevant for models beyond a cosmological constant and may allow us to increase the dark energy Figure of Merit by at least a factor of three.

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arXiv2020

Euclid: impact of nonlinear prescriptions on cosmological parameter estimation from weak lensing cosmic shear

Upcoming surveys will map the growth of large-scale structure with unprecented precision, improving our understanding of the dark sector of the Universe. Unfortunately, much of the cosmological information is encoded by the small scales, where the clustering of dark matter and the effects of astrophysical feedback processes are not fully understood. This can bias the estimates of cosmological parameters, which we study here for a joint analysis of mock Euclid cosmic shear and Planck cosmic microwave background data. We use different implementations for the modelling of the signal on small scales and find that they result in significantly different predictions. Moreover, the different nonlinear corrections lead to biased parameter estimates, especially when the analysis is extended into the highly nonlinear regime, with both the Hubble constant, $H_0$, and the clustering amplitude, $σ_8$, affected the most. Improvements in the modelling of nonlinear scales will therefore be needed if we are to resolve the current tension with more and better data. For a given prescription for the nonlinear power spectrum, using different corrections for baryon physics does not significantly impact the precision of Euclid, but neglecting these correction does lead to large biases in the cosmological parameters. In order to extract precise and unbiased constraints on cosmological parameters from Euclid cosmic shear data, it is therefore essential to improve the accuracy of the recipes that account for nonlinear structure formation, as well as the modelling of the impact of astrophysical processes that redistribute the baryons.

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