Formation and Evolution of
Galaxy Clusters Across Cosmic Time

In this work we aim for searching for strongly lensed QSOs in the J-PAS survey using a convolutional neural network (CNN). The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) is an ongoing survey that will cover at least 8000 square degrees of the northern hemisphere extragalactic sky in approximately 5 years, using an innovative system of 54 optical narrow band filters + 2 medium band filters. This large number of photometric bands in J-PAS can be really helpful when detecting strong lensing systems, where usually faint blue background galaxies (usually with emission lines) are lensed by massive red foreground galaxies. We have created simulations of strong lensing involving QSOs using real and mock data from the J-PAS survey. Our simulations of lensed QSOs, together with non-lensed examples, have been used to train the CNN, yielding promising results.