arXiv subjects

Santiago Casas

Publications and source records attributed to Santiago Casas.

At least 19 recordsLinked to original sources

arXiv2026

Inferring cosmological parameters from galaxy and dark sirens cross-correlation

The number of observed gravitational wave (GW) events is growing fast thanks to rapidly improving detector sensitivities. GWs from compact binary coalescences like Black Holes or Neutron Stars behave like standard sirens and can be used as cosmological probes. To this aim, generally, the observation of an electromagnetic counterpart and the measurement of the redshift are needed. However, even when those are not available, it is still possible to exploit these "dark sirens" via statistical methods. In this work, we explore a method that exploits the information contained in the cross-correlation of samples of GW events with matter over-density tracers like galaxy catalogues. Contrary to other currently employed dark-sirens methods, this approach does not suffer from systematic errors related to the incompleteness of the galaxy catalogue. To further enhance the technique, we implement tomography in redshift space for the galaxy catalogue and luminosity distance space for the GWs. We simulate future data collected by the array of currently existing detectors, namely LIGO, Virgo, and Kagra, as well as planned third-generation ones such as the Einstein Telescope and Cosmic Explorers. We cross-correlate these data with those from upcoming photometric galaxy surveys such as Euclid. We perform a sensitivity forecast employing a full-likelihood approach and explore the parameter space with Monte Carlo Markov Chains. We find that with this method, third-generation detectors will be able to determine the Hubble constant $H_0$ with an error of only 0.7%, which is enough to provide decisive information to shed light on the Hubble tension. Furthermore, for the other cosmological parameters, we find that the GWs and galaxy surveys information are highly complementary, and the use of both significantly improves the ability to constrain the underlying cosmology.

astro-ph.CO↗

arXiv2026

cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era

cloelib is a Python library developed to compute cosmological observables within the Cosmology Likelihood for Observables in Euclid (CLOE) ecosystem (cloe-org). As cosmology enters a precision era driven by galaxy survey missions such as Euclid, there is a growing need for flexible, efficient, and differentiable software capable of supporting next-generation inference pipelines. cloelib addresses these demands through a modular architecture that interfaces seamlessly with established Boltzmann solvers whilst incorporating JAX-based automatic differentiation to enable gradient-based methods. The library defines consistent protocols for background evolution, perturbations, and non-linear structure formation, and supports a wide range of observables, including photometric and spectroscopic large-scale structure probes, as well as cross-correlations with the Cosmic Microwave Background and galaxy clusters. In its finalised form, cloelib is intended to serve as the reference theory computation infrastructure for Euclid's first cosmological release, bridging traditional numerical cosmology with modern optimisation techniques and emerging machine learning approaches to inference.

astro-ph.CO↗

arXiv2026

cloelike: A Python Library for Cosmological Likelihood Inference in the Euclid Era

cloelike is a Python package providing modular, composable Gaussian likelihood classes for the main cosmological large-scale structure observables targeted by the ESA Euclid space mission. It is a core component of the CLOE (Cosmology Likelihood for Observables in Euclid) ecosystem and interfaces directly with cloelib for theoretical predictions and euclidlib for reading official Euclid data products. The package implements Gaussian likelihoods covering harmonic angular power spectra and real-space two-point correlation functions for weak lensing (WL), photometric galaxy clustering (GCph), and Galaxy-Galaxy Lensing (GGL) in all joint probe combinations (3x2pt, 2x2pt), as well as spectroscopic full-shape power spectrum multipoles, and baryonic Acoustic oscillations (BAO). cloelike is actively used in internal Euclid Consortium analyses and is openly released to support community validation and reproducibility.

astro-ph.CO↗

arXiv2025

CLAPP: The CLASS LLM Agent for Pair Programming

We introduce CLAPP (CLASS LLM Agent for Pair Programming), an interactive AI assistant designed to support researchers working with the Einstein-Boltzmann solver CLASS. CLAPP leverages large language models (LLMs) and domain-specific retrieval to provide conversational coding support for CLASS-answering questions, generating code, debugging errors, and producing plots. Its architecture combines multi-agent LLM orchestration, semantic search across CLASS documentation, and a live Python execution environment. Deployed as a user-friendly web application, CLAPP lowers the entry barrier for scientists unfamiliar with AI tools and enables more productive human-AI collaboration in computational and numerical cosmology. The app is available at https://classclapp.streamlit.app

astro-ph.IM↗

arXiv2025

Open Source Planning & Control System with Language Agents for Autonomous Scientific Discovery

We present a multi-agent system for automation of scientific research tasks, cmbagent (https://github.com/CMBAgents/cmbagent). The system is formed by about 30 Large Language Model (LLM) agents and implements a Planning & Control strategy to orchestrate the agentic workflow, with no human-in-the-loop at any point. Each agent specializes in a different task (performing retrieval on scientific papers and codebases, writing code, interpreting results, critiquing the output of other agents) and the system is able to execute code locally. We successfully apply cmbagent to carry out a PhD level cosmology task (the measurement of cosmological parameters using supernova data) and evaluate its performance on two benchmark sets, finding superior performance over state-of-the-art LLMs. The source code is available on GitHub, demonstration videos are also available, and the system is deployed on HuggingFace and will be available on the cloud.

cs.AI↗

arXiv2025

DESI forecast for Dark Matter-Neutrino interactions using EFTofLSS

We apply the Effective Field Theory of Large Scale Structure (EFTofLSS) to non-standard models of dark matter with suppressed small-scale structure imprinted by early-time physics, here exemplified by interacting dark matter (IDM) coupled to standard model neutrinos, and cross-check that the EFTofLSS has no trouble replicating the real-space halo-halo power spectrum from N-body simulations. We perform forecasts for a DESI ELG-like experiment using the redshift-space power spectrum and find that, under very conservative priors on these parameters, the EFTofLSS is not expected to yield strong constraints on dark matter interactions. However, with a better understanding of the evolution of counterterms and stochastic terms with redshift, realistic IDM models could in principle be detected using the full-shape power spectrum analysis of such a spectroscopic galaxy survey.

astro-ph.CO↗

arXiv2025

Model-independent forecasts for the cosmological anisotropic stress

The effective anisotropic stress $η$ is a key variable in the characterization of many classes of modified gravity theories, as it allows the testing for a long-range force additional to gravity. In this paper we forecast the precision with which future large surveys can determine $η$ in a way that only relies on directly observable quantities obtained from the spectroscopic measurements of the clustering of galaxies and the photometric based observation of the projected lensing and galaxy clustering correlations and their cross signal. Our method does not require further assumptions about the initial power spectrum, the modified gravity model, the expansion rate, or the bias. We consider various cases: $η$ free to vary in space and time, or with only redshift dependence, or constant. We take as a reference specifications that approximate a Euclid-like photometric or a combined one with a DESI-like spectroscopic survey. Among our results, we find that a future large-scale lensing and clustering survey can constrain $η$ to at least 30\% if $z$, $k$ independent, and to less than 10\% on average for the $z$ dependence only, to finally reach 5\% values in the constant case.

astro-ph.CO↗

arXiv2024

TOPO: Time-Ordered Provable Outputs

We present TOPO (Time-Ordered Provable Outputs), a tool designed to enhance reproducibility and data integrity in astrophysical research, providing a trustless alternative to data analysis blinding. Astrophysical research frequently involves probabilistic algorithms, high computational demands, and stringent data privacy requirements, making it difficult to guarantee the integrity of results. TOPO provides a secure framework for verifying reproducible data analysis while ensuring sensitive information remains hidden. Our approach utilizes deterministic hashing to generate unique digital fingerprints of outputs, and Merkle Trees to store outputs in a time-ordered manner. This enables efficient verification of specific components or the entire dataset while making it computationally infeasible to manipulate results - thereby mitigating the risk of human interference and confirmation bias, key objectives of blinding methods. We demonstrate TOPO's utility in a cosmological context using TOPO-Cobaya, showcasing how blinding and verification can be seamlessly integrated into Markov Chain Monte Carlo calculations, rendering the process cryptographically provable. This method addresses pressing challenges in the reproducibility crisis and offers a robust, verifiable framework for astrophysical data analysis.

astro-ph.IM↗

arXiv2024

CosmoAmautas: Astrophysics in the high school classroom (2nd edition)

We present the second edition of the book `CosmoAmautas: Astrophysics in the classroom' which is a text and activity book on selected topics in astrophysics. The content is written in Spanish and intended as the introductory literature and material for high school teachers who want to integrate astronomy to their science and math classes. The book includes an introduction to topics such as planetary science, stellar evolution, exoplanets, galaxies, black holes, and cosmology. In addition to the astronomy content, the book includes didactic notes on general physics of gravity and light, unit conversion, history of science, and tools for the digital classroom (ICT tools), which are compatible with the requirements of the Peruvian high school curriculum. This book is constructed based on the astrophysics curriculum and education model introduced in the online teacher-training workshop CosmoAmautas, which took place in 2021 and 2022. CosmoAmautas (amauta = teacher in the Quechua language) is an astronomy education project in Peru, funded by the IAU Office of Astronomy for Development. For more information, please visit www.cosmoamautas.org.

physics.ed-ph↗

arXiv2024

Non-linear power spectrum and forecasts for Generalized Cubic Covariant Galileon

To fully exploit the data from next generation surveys, we need an accurate modelling of the matter power spectrum up to non-linear scales. Therefore in this work we present the halo model reaction framework for the Generalized Cubic Covariant Galileon (GCCG) model, a modified gravity model within the Horndeski class of theories which extends the cubic covariant Galileon (G3) by including power laws of the derivatives of the scalar field in the K-essence and cubic terms. We modify the publicly available software ReACT for the GCCG in order to obtain an accurate prediction of the non-linear power spectrum. In the limit of the G3 model we compare the modified ReACT code to $N$-body simulations and we find agreement within 5\% for a wide range of scales and redshifts. We then study the relevant effects of the modifications introduced by the GCCG on the non-linear matter power spectrum. Finally, we provide forecasts from spectroscopic and photometric primary probes by next generation surveys using a Fisher matrix method. We show that future data will be able to constrain at 1$σ$ the two additional parameters of the model at the percent level and that considering non-linear corrections to the matter power spectrum beyond the linear regime is crucial to obtain this result.

astro-ph.CO↗

arXiv2024

Stage-IV Cosmic Shear with Modified Gravity and Model-independent Screening

We forecast constraints on minimal model-independent parametrisations of several Modified Gravity theories using mock Stage-IV cosmic shear data. We include nonlinear effects and screening, which ensures recovery of General Relativity on small scales. We introduce a power spectrum emulator to accelerate our analysis and evaluate the robustness of the growth index parametrisation with respect to two cosmologies: $Λ$CDM and the normal branch of the DGP model. We forecast the uncertainties on the growth index $γ$ to be of the order $\sim 10\%$. We find that our halo-model based screening approach demonstrates excellent performance, meeting the precision requirements of Stage-IV surveys. However, neglecting the screening transition results in biased predictions for cosmological parameters. We find that the screening transition shows significant degeneracy with baryonic feedback, requiring a much better understanding of baryonic physics for its detection. Massive neutrinos effects are less prominent and challenging to detect solely with cosmic shear data.

astro-ph.CO↗

arXiv2024

CLASS-OneLoop: Accurate and Unbiased Inference from Spectroscopic Galaxy Surveys

The power spectrum is the most commonly applied summary statistics to extract cosmological information from the observed three-dimensional distribution of galaxies in spectroscopic surveys. We present CLASS-OneLoop, a new numerical tool, fully integrated into the Boltzmann code CLASS, enabling the calculation of the one-loop power spectrum of biased tracers in spectroscopic surveys. Built upon the Eulerian moment expansion framework for redshift-space distortions, the implemented model incorporates a complete set of nonlinear biases, counterterms, and stochastic contributions, and includes the infrared resummation and the Alcock-Paczynski effect. The code features an evaluation of the loops by either direct numerical integration or Fast Fourier Transform, and employs a fast-slow parameter decomposition, which is essential for accelerating MCMC runs. After presenting performance and validation tests, as an illustration of the capabilities of the code, we apply it to fit the measured redshift-space halo power spectrum wedges on a $Λ$CDM subset of the AbacusSummit simulation suite and considering scales up to $k_{\rm max} = 0.3\,h/$Mpc. We find that the one-loop model adeptly recovers the fiducial cosmology of the simulation, while a simplified model commonly used in the literature for sensitivity forecasts yields significantly biased results. Furthermore, we conduct Monte Carlo Markov Chain (MCMC) forecasts for a DESI-like survey, considering a model with a dynamical dark energy component. Our results demonstrate the ability to independently constrain cosmological and nuisance parameters, even in the presence of a large parameter space with twenty-nine variables.

astro-ph.CO↗

arXiv2023

JAX-COSMO: An End-to-End Differentiable and GPU Accelerated Cosmology Library

We present jax-cosmo, a library for automatically differentiable cosmological theory calculations. It uses the JAX library, which has created a new coding ecosystem, especially in probabilistic programming. As well as batch acceleration, just-in-time compilation, and automatic optimization of code for different hardware modalities (CPU, GPU, TPU), JAX exposes an automatic differentiation (autodiff) mechanism. Thanks to autodiff, jax-cosmo gives access to the derivatives of cosmological likelihoods with respect to any of their parameters, and thus enables a range of powerful Bayesian inference algorithms, otherwise impractical in cosmology, such as Hamiltonian Monte Carlo and Variational Inference. In its initial release, jax-cosmo implements background evolution, linear and non-linear power spectra (using halofit or the Eisenstein and Hu transfer function), as well as angular power spectra with the Limber approximation for galaxy and weak lensing probes, all differentiable with respect to the cosmological parameters and their other inputs. We illustrate how autodiff can be a game-changer for common tasks involving Fisher matrix computations, or full posterior inference with gradient-based techniques. In particular, we show how Fisher matrices are now fast, exact, no longer require any fine tuning, and are themselves differentiable. Finally, using a Dark Energy Survey Year 1 3x2pt analysis as a benchmark, we demonstrate how jax-cosmo can be combined with Probabilistic Programming Languages to perform posterior inference with state-of-the-art algorithms including a No U-Turn Sampler, Automatic Differentiation Variational Inference,and Neural Transport HMC. We further demonstrate that Normalizing Flows using Neural Transport are a promising methodology for model validation in the early stages of analysis.

astro-ph.CO↗

arXiv2022

Constraining gravity with synergies between radio and optical cosmological surveys

In this work we present updated forecasts on parameterised modifications of gravity that can capture deviations of the behaviour of cosmological density perturbations beyond $Λ$CDM. For these forecasts we adopt the SKA Observatory (SKAO) as a benchmark for future cosmological surveys at radio frequencies, combining a continuum survey for weak lensing and angular galaxy clustering with an HI galaxy survey for spectroscopic galaxy clustering that can detect baryon acoustic oscillations and redshift space distortions. Moreover, we also add 21cm HI intensity mapping, which provides invaluable information at higher redshifts, and can complement tomographic resolution, thus allowing us to probe redshift-dependent deviations of modified gravity models. For some of these cases, we combine the probes with other optical surveys, such as the Dark Energy Spectroscopic Instrument (DESI) and the Vera C. Rubin Observatory (VRO). We show that such synergies are powerful tools to remove systematic effects and degeneracies in the non-linear and small-scale modelling of the observables. Overall, we find that the combination of all SKAO radio probes will have the ability to constrain the present value of the functions parameterising deviations from $Λ$CDM ($μ$ and $Σ$) with a precision of $2.7\%$ and $1.8\%$ respectively, competitive with the constraints expected from optical surveys and with constraints we have on gravitational interactions in the standard model. Exploring the radio-optical synergies, we find that the combination of VRO with SKAO can yield extremely tight constraints on $μ$ and $Σ$ ($0.9\%$ and $0.7\%$ respectively), which are further improved when the cross-correlation between intensity mapping and DESI galaxies is included.

astro-ph.CO↗

arXiv2022

Testing Screened Modified Gravity

Long range scalar fields with a coupling to matter appear to violate known bounds on gravitation in the solar system and the laboratory. This is evaded thanks to screening mechanisms. In this short review, we shall present the various screening mechanisms from an effective field theory point of view. We then investigate how they can and will be tested in the laboratory and on astrophysical and cosmological scales.

gr-qc↗

arXiv2021

Cosmological Tests of Gravity: A Future Perspective

In this review, we outline the expected tests of gravity that will be achieved at cosmological scales in the upcoming decades. We focus mainly on constraints on phenomenologically parameterized deviations from general relativity, which allow to test gravity in a model-independent way, but also review some of the expected constraints obtained with more physically motivated approaches. After reviewing the state-of-the-art for such constraints, we outline the expected improvement that future cosmological surveys will achieve, focusing mainly on future large-scale structures and cosmic microwave background surveys but also looking into novel probes on the nature of gravity. We will also highlight the necessity of overcoming accuracy issues in our theoretical predictions, issues that become relevant due to the expected sensitivity of future experiments.

astro-ph.CO↗

arXiv2021

Quintessential $α$-attractor inflation: forecasts for Stage IV galaxy surveys

Single-field models of $α$-attractor quintessential inflation provide a unified picture of the two periods of early- and late-time cosmic acceleration, where both inflation and dark energy are described by a single scalar degree of freedom rolling down a runaway potential. These theoretically well-motivated models have distinct observational predictions that are in agreement with existing cosmological data. We show that the next generation of large-scale structure surveys, even when no other cosmological data sets are considered, will strongly constrain the parameter space of these models, and test them against the standard cosmological model and more conventional non-quintessential inflation. In particular, we expect $\mathcal{O}(10^{-5}\mathrm{-}10^{-4})$ constraints on the present values of the dark energy equation of state and its time derivative, $w_0$ and $w_a$. We also forecast more than one order of magnitude tighter constraints on the spectral index of primordial curvature perturbations $n_s$ compared to the expectations for the standard model. This demonstrates the powerful synergy between the upcoming large-scale structure probes of inflation and those aiming to measure the tensor-to-scalar ratio $r$ through the observation of $B$-mode polarization of the cosmic microwave background.

astro-ph.CO↗

arXiv2020

Hybrid $P_{\ell}(k)$: general, unified, non-linear matter power spectrum in redshift space

Constraints on gravity and cosmology will greatly benefit from performing joint clustering and weak lensing analyses on large-scale structure data sets. Utilising non-linear information coming from small physical scales can greatly enhance these constraints. At the heart of these analyses is the matter power spectrum. Here we employ a simple method, dubbed "Hybrid $P_\ell(k)$", based on the Gaussian Streaming Model (GSM), to calculate the quasi non-linear redshift space matter power spectrum multipoles. This employs a fully non-linear and theoretically general prescription for the matter power spectrum. We test this approach against comoving Lagrangian acceleration simulation measurements performed in GR, DGP and $f(R)$ gravity and find that our method performs comparably or better to the dark matter TNS redshift space power spectrum model for dark matter. When comparing the redshift space multipoles for halos, we find that the Gaussian approximation of the GSM with a linear bias and a free stochastic term, $N$, is competitive to the TNS model. Our approach offers many avenues for improvement in accuracy as well as further unification under the halo model.

astro-ph.CO↗