H II regions are ionized nebulae associated with the formation of massive stars. They exhibit a wealth of emission lines in their spectra that form the basis for estimation of chemical composition. The amount of heavy chemical elements is essential to the understanding of important phenomena such as nucleosynthesis, star formation and chemical evolution of galaxies. For over 80 years, however, a discrepancy exists of a factor of around two between heavy-element abundances (the so-called metallicity) derived from the two main kinds of emission lines that can be measured in nebular spectra
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
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
