arXiv subjects

C. García-García

Publications and source records attributed to C. García-García.

5 recordsLinked to original sources

arXiv2026

An LSST-DESC Precursor Project: Hyper Suprime-Cam Year 1 $3\times2$pt in Harmonic Space

We present the first fully photometric joint analysis of weak gravitational lensing and galaxy clustering (3$\times$2pt) in harmonic space with LSST-DESC analysis pipelines applied to Hyper Suprime-Cam Year 1 (HSC Y1) data. The HSC Y1 dataset, with imaging depth and galaxy number density similar to those expected for the first year of LSST observations, is an ideal testbed for validating DESC measurement and inference tools. We measure the full set of angular power spectra - cosmic shear, galaxy clustering, and galaxy-galaxy lensing - perform null tests, and correct for the impact of observing conditions on both the galaxy density and shear fields via mode deprojection. We validate our likelihood pipeline by reproducing the official HSC Y1 cosmic shear cosmological constraints with the DESC inference code. Jointly analysing all three two-point functions, we constrain $Λ$CDM and $w$CDM cosmologies, reporting results for cosmic shear, the combination of galaxy clustering and galaxy-galaxy lensing (2$\times$2pt), and the full 3$\times$2pt. From the joint 3$\times$2pt $Λ$CDM analysis we find $Ω_m = 0.249^{+0.061}_{-0.051}$, $σ_8 = 0.904^{+0.098}_{-0.091}$, and $S_8 \equiv σ_8\sqrt{Ω_m/0.3} = 0.821^{+0.018}_{-0.021}$. This analysis validates the complete DESC 3x2pt infrastructure on survey data, providing the foundation for the forthcoming LSST Year 1 cosmological analysis.

astro-ph.CO↗

arXiv2026

\textit{Euclid} preparation. Baryon acoustic oscillations extraction techniques: comparison and optimisation

We present the first end-to-end validation of the Euclid baryon acoustic oscillation (BAO) analysis pipeline, encompassing density-field reconstruction, two-point correlation function measurement, and cosmological-parameter inference. Using eight Euclid-like mock catalogues from each of four Flagship I snapshots, designed to reproduce the expected statistical properties of the first Euclid data release (DR1), we assess the two standard BAO reconstruction methods based on the Zel'dovich approximation, RecSym and RecIso, across $0.9 \leq z \leq 1.8$. The pipeline introduces several methodological advances: an emulator-based model evaluator (Bora.jl) combined with a Hamiltonian Monte Carlo sampler (NUTS), achieving more than a 500-fold speed-up relative to standard Markov chain Monte Carlo, and a semi-analytical covariance estimator (BeXiCov+WinCov) that enables robust error estimates from only eight mock realisations while remaining stable under fiducial-cosmology variations. These components ensure computational efficiency while reducing the risk of underestimating parameter uncertainties. Both reconstruction schemes yield unbiased BAO measurements across all redshifts and analysis choices, including smoothing scale and fiducial cosmology. In each snapshot, reconstruction enhances the figure of merit for $\{Ω_m, H_0 r_s\}$ by $\sim3$, equivalent to tripling the effective survey volume. Combining the four redshift bins, the improvement remains substantial, with BAO-only constraints reaching $\sim10\%$ precision on $Ω_m$ and $\sim3\%$ on $H_0 r_s$. Results from RecSym and RecIso are consistent within uncertainties, though we recommend RecSym during testing due to its lower sensitivity to covariance variations. These findings establish the accuracy, robustness, and scalability of the Euclid BAO pipeline for DR1, providing a solid foundation for future cosmological analyses.

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↗

arXiv2024

Growth history and quasar bias evolution at z < 3 from Quaia

We make use of the Gaia-Unwise quasar catalogue, Quaia, to constrain the growth history out to high redshifts from the clustering of quasars and their cross-correlation with maps of the Cosmic Microwave Background (CMB) lensing convergence. Considering three tomographic bins, centered at redshifts $\bar{z}_i = [0.69, 1.59, 2.72]$, we reconstruct the evolution of the amplitude of matter fluctuations $σ_8(z)$ over the last $\sim12$ billion years of cosmic history. In particular, we make one of the highest-redshift measurements of $σ_8$ ($σ_8(z=2.72)=0.22\pm 0.06$), finding it to be in good agreement (at the $\sim1σ$ level) with the value predicted by $Λ$CDM using CMB data from Planck. We also used the data to study the evolution of the linear quasar bias for this sample, finding values similar to those of other quasar samples, although with a less steep evolution at high redshifts. Finally, we study the potential impact of foreground contamination in the CMB lensing maps and, although we find evidence of contamination in cross-correlations at $z\sim1.7$ we are not able to clearly pinpoint its origin as being Galactic or extragalactic. Nevertheless, we determine that the impact of this contamination on our results is negligible.

astro-ph.CO↗

arXiv2023

The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST

We present TXPipe, a modular, automated and reproducible pipeline for ingesting catalog data and performing all the calculations required to obtain quality-assured two-point measurements of lensing and clustering, and their covariances, with the metadata necessary for parameter estimation. The pipeline is developed within the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC), and designed for cosmology analyses using LSST data. In this paper, we present the pipeline for the so-called 3x2pt analysis -- a combination of three two-point functions that measure the auto- and cross-correlation between galaxy density and shapes. We perform the analysis both in real and harmonic space using TXPipe and other LSST-DESC tools. We validate the pipeline using Gaussian simulations and show that it accurately measures data vectors and recovers the input cosmology to the accuracy level required for the first year of LSST data under this simplified scenario. We also apply the pipeline to a realistic mock galaxy sample extracted from the CosmoDC2 simulation suite (Korytov et al. 2019). TXPipe establishes a baseline framework that can be built upon as the LSST survey proceeds. Furthermore, the pipeline is designed to be easily extended to science probes beyond the 3x2pt analysis.

astro-ph.CO↗