In the 90s, the COBE satellite discovered that not all the microwave emission from our Galaxy behaved as expected. Part of this signal was later assigned to a fresh new emission component, spatially correlated with the Galactic dust emission, which showed greater importance in the microwave range of frequencies. It has been named since as “anomalous microwave emission”, or AME. The current main hypothesis to explain the AME origin is that it is emitted by small dust particles which undergo fast spinning movements. In Fernández-Torreiro et al. (2023), we study the observational properties of

The amount and complexity of data delivered by modern galaxy surveys has been steadily increasing over the past years. New facilities will soon provide imaging and spectra of hundreds of millions of galaxies. Extracting coherent scientific information from these large and multi-modal data sets remains an open issue for the community and data-driven approaches such as deep learning have rapidly emerged as a potentially powerful solution to some long lasting challenges. This enthusiasm is reflected in an unprecedented exponential growth of publications using neural networks, which have gone

It is well known that fullerenes – big, complex, and highly resistant carbon molecules with potential applications in nanotechnology – are mostly seen in planetary nebulae (PNe); old dying stars with progenitor masses similar to our Sun. Fullerenes, like C60 and C70, have been detected in PNe whose infrared (IR) spectra are dominated by broad unidentified IR (UIR) plateau emissions. The identification of the chemical species (structure and composition) responsible for such UIR emission widely present in the Universe is a mystery in astrochemistry; although they are believed to be carbon-rich