We present a new spectroscopic study of 175 stars in the vicinity of the dwarf galaxy Hercules (d ~ 132 kpc) with data from the Anglo-Australian Telescope and its AAOmega spectrograph together with the Two Degree Field multi-object system to solve the conundrum that whether Hercules is tidally disrupting. We combine broad-band photometry, proper

Using MUSE data, we investigate the radial gradients of stellar population properties (namely age, [M/H], and the abundance ratio of α elements [α/Fe]) for a sample of nine dwarf early-type (dE) galaxies with log(M ⋆/M ⊙) ~ 9.0 and an infall time onto the Virgo cluster of 2-3 Gyr ago. We followed a similar approach as in Bidaran et al. to derive

The fiducial cosmological analyses of imaging surveys like DES typically probe the Universe at redshifts z < 1. We present the selection and characterization of high-redshift galaxy samples using DES Year 3 data, and the analysis of their galaxy clustering measurements. In particular, we use galaxies that are fainter than those used in the previous

We measure the [α/Fe] abundances for 183 quiescent galaxies at z = 0.60-0.75 with stellar masses ranging 10.4 ≤ log 10(M */M ⊙) ≤ 11.6 selected from the Large Early Galaxy Astrophysics Census survey. We estimate [α/Fe] from the ratio of the spectral indices Mgb (λ ~ 5177 Å) and Fe4383, compared to predictions of simple stellar population models. We

Reliable tools to extract patterns from high-dimensionality spaces are becoming more necessary as astronomical data sets increase both in volume and complexity. Contrastive Learning is a self-supervised machine learning algorithm that extracts informative measurements from multidimensional data sets, which has become increasingly popular in the

We computed the evidence in favour of two models, one based on field-aligned thermal conduction alone and another that includes thermal misbalance as well, to explain the damping of slow magneto-acoustic waves in hot coronal loops. Our analysis is based on the computation of the marginal likelihood and the Bayes factor for the two damping models