Many white dwarf stars show signs of having accreted smaller bodies, implying that they may host planetary systems. A small number of these systems contain gaseous debris discs, visible through emission lines. We report a stable 123.4-minute periodic variation in the strength and shape of the Ca II emission line profiles originating from the debris

Planetary nebulae (PNe) are excellent tracers of stellar populations with low surface brightness, and therefore provide a powerful method to detect and explore the rich system of substructures discovered around the main spiral galaxies of the Local Group. A search of PNe at the outskirts of the spiral galaxy M33 has been performed over a set of

Planes of satellites are observed in the Milky Way and Andromeda, and recent observations claim their presence as well in other nearby galactic systems. Moreover, recent proper motion data of MW satellites allege an important fraction of satellites are co-orbiting within the plane they define. However, the quality and degree of co-orbitation of the

A large number of Ultra-Diffuse Galaxies (UDGs) has been detected over the past few years, both in clusters and in isolation. UDGs have stellar masses typical of dwarf galaxies but effective radii of Milky Way-sized objects, and their origin remains puzzling. Using hydrodynamical zoom-in simulations from the NIHAO project we show that UDGs form

True Seyfert 2 candidates are those Seyferts galaxies whose optical spectral do not show broad lines, nevertheless in the X-ray domain, they exhibit some characteristic behavior of Seyferts 1 such as lack of X-ray obscuration and/or short timescale variability. A true 2 candidate will be confirmed as a true Seyfert 2 if the lack of its broad line

Deep learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much