In the last decade, machine learning and neural networks have emerged as powerful tools for analyzing huge collections of solar data, demonstrating versatility in tasks ranging from image reconstruction to the acceleration of spectropolarimetric inversions. However, while these algorithms offer unprecedented speed, they often lack the precision

TBD

I will review our current knowledge about the structure and stellar population of the Galactic bulge and of its Nuclear region, spatially overlapping with the Central Molecular Zone. I will also present new photometric and spectroscopic programs that will target the bulge innermost region in the next few years, promising to transform our

En este Trabajo de Fin de Máster se desarrolla y evalúa un sistema de Deep Learning guiado por la física para la reconstrucción de imágenes astronómicas de estrellas individuales y binarias adquiridas por el instrumento FastCam. El modelo integra redes convolucionales y capas recurrentes (LSTM) para modelar la correlación temporal de las

The WST project aims to design and construct an innovative 10-metre class wide-field spectroscopic survey telescope (WST) in the southern hemisphere. It will feature the parallel operation of two cutting-edge instruments: a high-multiplex (30,000), large field-of-view (3 square degrees) multi-object spectrograph (MOS) operating in both low- and