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Daniel de Andrés

Publications and source records attributed to Daniel de Andrés.

3 recordsLinked to original sources

The Three Hundred project: cosmic web identification from 2D gas and Compton-$y$ maps of galaxy clusters outskirts

Galaxy clusters are located at the nodes of the filamentary network known as the cosmic web. A more comprehensive understanding of galaxy clusters can be achieved by considering their environment, in particular, the filamentary structures to which they are connected. In this work, we aim to assess the reliability of the cosmic web reconstruction from mock observational data. In particular, we aim to quantify the effects of the 2D projection relative to the underlying 3D network and the impact of using the Sunyaev-Zel'dovich (SZ) effect as a tracer of the cosmic web. We reconstruct the filamentary networks in the outskirts of The Three Hundred simulated clusters with the filament finder DisPerSE. First, we extract the networks from the 2D gas distribution and evaluate their purity and completeness with respect to the 3D networks projected along the line of sight. We also compute the distances between the corresponding skeletons. Moreover, we identify filaments from simulated Compton-$y$ maps of the clusters at redshift $z=0$, and we compare them with the 2D gas network. The skeletons extracted from 2D maps provide good representations of the underlying 3D ones, both in terms of critical points and filaments. We find a median distance between the spines of the 2D and projected 3D networks of approximately $0.22 \, h^{-1}$ Mpc, although the connectivity derived from the 2D networks is slightly underestimated. We observe a good spatial agreement between the gas and SZ networks, with a median distance of $\approx 0.24 \, h^{-1}$ Mpc. Finally, we show that gas outside galaxy clusters is preferentially located in filamentary structures, which contribute $\sim 80\%$ of the integrated Compton-$Y$ parameter of clusters' outskirts.

astro-ph.CO↗

Machine Learning applications to Galaxy Clusters

This chapter reviews the application of Artificial Intelligence (AI) techniques to the study of galaxy clusters, covering both theoretical developments and their use as tools to infer cluster properties from a variety of observational tracers. We discuss recent advances in mass estimation from SZ, X-ray, optical, and dynamical data, highlighting the ability of AI methods to capture non-linear features, projection effects, and complex cluster morphologies beyond more classical approaches. In addition, we present other emerging applications, including the emulation of baryonic physics from N-body simulations, the characterization of dynamical states and mergers, and the analysis of the diffuse components such as the intracluster light. Particular emphasis is placed on the role of simulations in training these models, the impact of baryonic modelling, and the need for a robust uncertainty quantification and interpretability. Finally, we outline current limitations and future prospects, stressing the importance of combining flexible simulation strategies with AI techniques to fully exploit next-generation surveys for precision cosmology.

astro-ph.CO↗

Anisotropic deformations in a class of projectively-invariant metric-affine theories of gravity

Among the general class of metric-affine theories of gravity, there is a special class conformed by those endowed with a projective symmetry. Perhaps the simplest manner to realise this symmetry is by constructing the action in terms of the symmetric part of the Ricci tensor. In these theories, the connection can be solved algebraically in terms of a metric that relates to the spacetime metric by means of the so-called deformation matrix that is given in terms of the matter fields. In most phenomenological applications, this deformation matrix is assumed to inherit the symmetries of the matter sector so that in the presence of an isotropic energy-momentum tensor, it respects isotropy. In this work we discuss this condition and, in particular, we show how the deformation matrix can be anisotropic even in the presence of isotropic sources due to the non-linear nature of the equations. Remarkably, we find that Eddington-inspired-Born-Infeld theories do not admit anisotropic deformations, but more general theories do. However, we find that the anisotropic branches of solutions are generally prone to a pathological physical behaviour.

gr-qc↗