arXiv subjects

Gabriel S. M. Teixeira

Publications and source records attributed to Gabriel S. M. Teixeira.

4 recordsLinked to original sources

arXiv2026

Caught in the web: galaxy mergers along cosmic filaments

Galaxy clusters grow through the accretion of galaxies from groups, filaments, and other clusters. During this process, galaxies may undergo pre-processing in lower-density environments, where galaxy-galaxy mergers and other interactions can significantly alter their properties prior to cluster infall. We investigate the role of galaxy mergers in the pre-processing of galaxies prior to cluster infall by studying the spatial distribution of mergers across the cosmic web. We use a sample of 43,922 galaxies targeted by the 4MOST CHANCES survey in and around 33 low-redshift clusters (z < 0.07). Using Zoobot, a deep-learning framework trained on Galaxy Zoo data, we identify 698 galaxy mergers. We measure their distances to cosmic web filaments and compare them with those of non-merging galaxies. We find that galaxy mergers are significantly closer to filaments than the non-merging galaxy population, with this trend being strongest beyond the cluster virial radius. This suggests that filaments provide conditions conducive to mergers, possibly moderating relative velocities and enhancing gas availability. Our findings support a scenario in which filaments play a key role in transforming galaxies through pre-processing by promoting mergers before they enter cluster cores where star formation quenches.

astro-ph.GA↗

arXiv2025

Symbolic Regression Is All You Need: From Simulations to Scaling Laws in Binary Neutron Star Mergers

Gravitational wave sources with electromagnetic counterparts have highlighted the need for predictive, interpretable models linking the parameters of compact binary systems to post-merger remnants and mass outflows. In this work, we explore AI-driven symbolic regression (SR) frameworks to derive updated analytical relations for disk ejecta mass in binary neutron star mergers, trained on state-of-the-art numerical relativity simulations. Our method reveals a set of compact equations that outperform existing fitting formulae across multiple statistical metrics while remaining physically interpretable. Notably, SR also enables alternative predictor sets (e.g., $\{M_1,M_2,\tildeΛ\}$) that match or exceed the accuracy of models relying solely on compactness of the lightest neutron star ($C_1$), enabling new parameter constraints from electromagnetic observations. Unlike traditional black-box machine learning models, these closed-form expressions generalize robustly to regions of the parameter space not represented in the training data, offering a physics-informed tool for multimessenger observations and constraints on the neutron star equation of state.

astro-ph.HE↗

arXiv2025

Targeting cluster galaxies for the 4MOST CHANCES Low-z sub-survey with photometric redshifts

The evolution of galaxies is shaped by both internal processes and their external environments. Galaxy clusters and their surroundings provide ideal laboratories to study these effects, particularly mechanisms such as quenching and morphological transformation. The Chilean Cluster galaxy Evolution Survey (CHANCES) Low-z sub-survey is part of the CHileAN Cluster galaxy Evolution Survey, a 4MOST community survey designed to uncover the relationship between the formation and evolution of galaxies and hierarchical structure formation as it happens, through deep and wide multi-object spectroscopy. We present the target selection strategy followed to select galaxy cluster candidate members for the CHANCES low-z sub-survey, in and around 50 clusters and two superclusters at z<0.07, out to (5XR200) and down to mr= 20.4. Combining public photometric redshift estimates from the DESI Legacy Imaging Survey and T80S/S-PLUS iDR5, with custom photometric redshifts, we identify likely galaxy cluster candidate members whose photometric redshifts are consistent with being at the known redshift of the cluster and measure the average deviations of their photometric redshifts with respect to the spectroscopic redshift measurements σNMAD. We have successfully compiled our CHANCES-low-redshift catalogues, split into three different sub-surveys: low-z bright (mr<18.5), low-z faint (18.5<=mr<20.4) and low-z faint supplementary, by selecting>= 500,000 galaxy cluster candidate members and including confirmed spectroscopic galaxy cluster members, from which we expect to obtain 4MOST low-resolution (R~6500) spectra for ~320,000 galaxies. The CHANCES Low-z target catalogues form a statistically robust sample for spectroscopic follow-up, allowing studies of galaxy evolution and environmental effects in nearby cluster and supercluster environments.

astro-ph.GA↗

arXiv2025

CHANCES, the Chilean Cluster Galaxy Evolution Survey: Selection and initial characterisation of clusters and superclusters

CHANCES, the CHileAN Cluster galaxy Evolution Survey, will study the evolution of galaxies in and around 100 massive galaxy clusters from the local Universe out to $z = 0.45$, and two superclusters at $z \sim 0.05$ that contain roughly 25 Abell clusters each. CHANCES will use the new 4MOST Spectroscopic Survey Facility on the VISTA 4m telescope to obtain spectra for $\sim$500,000 galaxies with magnitudes $r_\mathrm{AB} < 20.4$, providing comprehensive spectroscopic coverage of each cluster out to $5r_{200}$. Its wide and deep scope will trace massive and dwarf galaxies from the surrounding filaments and groups to the cores of galaxy clusters. This will enable the study of galaxy preprocessing and of the role of the evolving environment on galaxy evolution. In this paper, we present and characterise the sample of clusters and superclusters to be targeted by CHANCES. We used literature catalogues based on X-ray emission and the Sunyaev-Zel'dovich effect to define the cluster sample in a homogeneous way, with attention to cluster mass and redshift, as well as the availability of ancillary data. We calibrated literature mass estimates from various surveys against each other and provide an initial mass estimate for each cluster, which we used to define the radial extent of the 4MOST coverage. We also present an initial assessment of the structure surrounding these clusters based on the redMaPPer red-sequence algorithm as a preview of some of the science CHANCES will enable.

astro-ph.GA↗