arXiv subjects

Ignacio Quiroz

Publications and source records attributed to Ignacio Quiroz.

2 recordsLinked to original sources

arXiv2026

Fishing for Jellyfish Galaxies: Exploring ram-pressure stripping with crowd science

Aims: We present the first results of Fishing for Jellyfish Galaxies, a pilot citizen-science project using Zooniverse to identify galaxies undergoing ram-pressure stripping (RPS). Methods: Volunteers visually inspected colour images of late-type galaxies from the Dark Energy Camera Legacy Survey, from a sample of 49,703 galaxies selected within $4 \times R_{500}$ of clusters and groups, restricted to galaxies brighter than 19th magnitude in the g and r bands, and with a minimum half-light radius of 2 arcseconds, to aid classification. We detail our data processing, including debiasing classifications and optimising vote-fraction thresholds to maximise completeness and purity, calibrated against a ground-truth set of pre-labelled galaxies. Results: Our final catalogue contains 6739 jellyfish candidates (6621 new), 5430 merger candidates, and 29,729 undisturbed galaxies, with 3910 jellyfish exhibiting prominent tail-like morphologies. We find that the fraction of RPS candidates rises from ~10% in galaxy groups to ~20-30% in massive clusters, confirming the findings of previous studies carried out on smaller samples. For the subset of our RPS candidate sample with spectroscopic data, we measure a median clustercentric velocity 53% higher than the general cluster population, consistent with galaxies in early stages of accretion into the cluster. They are also typically late-type blue galaxies with elevated star-formation rates, in agreement with expectations. These results demonstrate that citizen scientists can reliably identify galaxies that undergo environmental processes. We provide the initial release of 37,599 visually classified galaxies as a resource for future studies of galaxy transformation in clusters.

astro-ph.GA↗

arXiv2025

The galaxy bias profile of cosmic voids

Cosmic voids are underdense regions within the large-scale structure of the Universe, spanning a wide range of physical scales - from a few megaparsecs (Mpc) to the largest observable structures. Their distinctive properties make them valuable cosmological probes and unique laboratories for galaxy formation studies. A key aspect to investigate in this context is the galaxy bias, $b$, within voids - that is, how galaxies in these underdense regions trace the underlying dark-matter density field. We want to measure the dependence of the large-scale galaxy bias on the distance to the void center, and to evaluate whether this bias profile varies with the void properties and identification procedure. We apply a void identification scheme based on spherical overdensities to galaxy data from the IllustrisTNG magnetohydrodynamical simulation. For the clustering measurement, we use an object-by-object estimate of large-scale galaxy bias, which offers significant advantages over the standard method based on ratios of correlation functions or power spectra. We find that the average large-scale bias of galaxies inside voids tends to increase with void-centric distance when normalized by the void radius. For the entire galaxy population within voids, the average bias rises with the density of the surrounding environment and, consequently, decreases with increasing void size. Due to this environmental dependence, the average galaxy bias inside S-type voids - embedded in large-scale overdense regions - is significantly higher ($\langle b\rangle_{\rm in} > 0$) at all distances compared to R-type voids, which are surrounded by underdense regions ($\langle b\rangle_{\rm in} < 0$). The bias profile for S-type voids is also slightly steeper. Since both types of voids host halo populations of similar mass, the measured difference in bias can be interpreted as a secondary bias effect.

astro-ph.CO↗