arXiv subjects

J. Ruiz-Zapatero

Publications and source records attributed to J. Ruiz-Zapatero.

4 recordsLinked to original sources

arXiv2026

Euclid preparation. CIV. Impact of galaxy intrinsic alignment modelling choices on Euclid 3x2pt cosmology

The Euclid galaxy survey will provide unprecedented constraints on cosmology, but achieving unbiased results will require an optimal characterisation and mitigation of systematic effects. The intrinsic alignments (IAs) of galaxies are one of the dominant contaminants of the weak lensing (WL) and galaxy-galaxy lensing (GGL) probes. In this work, we assess IA modelling choices for Euclid DR1 3x2pt analyses by using synthetic data vectors and comparing the performance of the two most commonly used IA models, non-linear alignment (NLA) and tidal alignment tidal torquing (TATT), along with several variations. Our analyses combine three perspectives: (i) the constraining power on the IA and cosmological parameters for each IA model, (ii) the bias that results when the IA analysis model differs from the model used to generate the synthetic data vector, and (iii) the degeneracies between IAs and photometric redshift (photo-z) nuisance parameters. Amongst the IA models analysed, the redshift-dependent TATT model (zTATT) provides the most flexible description of IAs, with a constraining power similar to simpler IA models, making it a suitable choice for Euclid DR1 3x2pt analyses.

astro-ph.CO↗

arXiv2026

Euclid preparation. LXXXIX. Accurate and precise data-driven angular power spectrum covariances

We develop techniques for generating accurate and precise internal covariances for measurements of clustering and weak-lensing angular power spectra. These methods have been designed to produce non-singular and unbiased covariances for Euclid's large anticipated data vector and will be critical for validation against observational systematic effects. We constructed jackknife segments that are equal in area to a high precision by adapting the binary space partition algorithm to work on arbitrarily shaped regions on the unit sphere. Jackknife estimates of the covariances are internally derived and require no assumptions about cosmology or galaxy population and bias. Our covariance estimation, called DICES (Debiased Internal Covariance Estimation with Shrinkage), first estimated a noisy covariance through conventional delete-1 jackknife resampling. This was followed by linear shrinkage of the empirical correlation matrix towards the Gaussian prediction, rather than linear shrinkage of the covariance matrix. Shrinkage ensures the covariance is non-singular and therefore invertible, which is critical for the estimation of likelihoods and validation. We then applied a delete-2 jackknife bias correction to the diagonal components of the jackknife covariance that removed the general tendency for jackknife error estimates to be biased high. We validated internally derived covariances, which used the jackknife resampling technique, on synthetic Euclid-like lognormal catalogues. We demonstrate that DICES produces accurate, non-singular covariance estimates, with the relative error improving by 33% for the covariance and 48% for the correlation structure in comparison to jackknife estimates. These estimates can be used for highly accurate regression and inference.

astro-ph.CO↗

arXiv2024

LimberJack.jl: auto-differentiable methods for angular power spectra analyses

We present LimberJack.jl, a fully auto-differentiable code for cosmological analyses of 2 point auto- and cross-correlation measurements from galaxy clustering, CMB lensing and weak lensing data written in Julia. Using Julia's auto-differentiation ecosystem, LimberJack.jl can obtain gradients for its outputs up to an order of magnitude faster than traditional finite difference methods. This makes LimberJack.jl greatly synergistic with gradient-based sampling methods, such as Hamiltonian Monte Carlo, capable of efficiently exploring parameter spaces with hundreds of dimensions. We first prove LimberJack.jl's reliability by reanalysing the DES Y1 3$\times$2-point data. We then showcase its capabilities by using a O(100) parameters Gaussian Process to reconstruct the cosmic growth from a combination of DES Y1 galaxy clustering and weak lensing data, eBOSS QSO's, CMB lensing and redshift-space distortions. Our Gaussian process reconstruction of the growth factor is statistically consistent with the $Λ$CDM Planck 2018 prediction at all redshifts. Moreover, we show that the addition of RSD data is extremely beneficial to this type of analysis, reducing the uncertainty in the reconstructed growth factor by $20\%$ on average across redshift. LimberJack.jl is a fully open-source project available on Julia's general repository of packages and GitHub.

astro-ph.CO↗

arXiv2021

Geometry vs growth: Internal consistency of the flat ΛCDM model with KiDS-1000

We carry out a multi-probe self-consistency test of the flat $Λ$CDM model with the aim of exploring potential causes of the reported tensions between high- and low-redshift cosmological observations. We divide the model into two theory regimes determined by the smooth background (geometry) and the evolution of matter density fluctuations (growth), each governed by an independent set of Lambda Cold Dark Matter ($Λ$CDM) cosmological parameters. This extended model is constrained by a combination of weak gravitational lensing measurements from the Kilo-Degree Survey, galaxy clustering signatures extracted from Sloan Digital Sky Survey campaigns and the Six-Degree Field Galaxy Survey, and the angular baryon acoustic scale and the primordial scalar fluctuation power spectrum measured in $\textit{Planck}$ cosmic microwave background (CMB) data. We find strong consistency between the geometry and growth parameters, and with the posterior of standard $Λ$CDM analysis. Tension in the amplitude of matter density fluctuations as measured by the parameter $S_8$ persists at around 3$σ$, with a $1.5\,\%$ constraint of $S_8 = 0.776_{-0.008}^{+0.016}$ for the combined probes. We also observe a less significant preference (at least $2σ$) for higher values of the Hubble constant, $H_0 = 70.5^{+0.7}_{-1.5}\,{\rm km\, s^{-1} Mpc^{-1}}$, as well as for lower values of the total matter density parameter $Ω_{\rm{m}} = 0.289^{+0.007}_{-0.005}$ compared to the full $\textit{Planck}$ analysis. Including the subset of the CMB information in the probe combination enhances these differences rather than alleviate them, which we link to the discrepancy between low and high multipoles in $\textit{Planck}$ data.

astro-ph.CO↗