The Active Phases of a Galaxy in the JWST and Euclid Era: From Radio Jets and Multiphase Outflows to Mergers

The objective of this thesis is to study the key processes that regulate the growth and evolution of galaxies, focusing on the role of active galactic nuclei (AGNs). AGN feedback, in the form of energy flows and radio jets, is a fundamental mechanism that regulates star formation, redistributes gas and dust, and shapes the structure of the host galaxy. Another phenomenon that affects galactic evolution is galaxy mergers, as these provide fresh gas, triggering starbursts and fueling black hole activity, sometimes leading to the formation of multiple AGNs within the same system. We first provide an overview of these phenomena, discussing AGN physics, feedback mechanisms, and the impact of galaxy mergers. We also include a brief chapter on the emerging role of machine learning in analyzing astronomical data that will be useful for the last chapter of this thesis. This thesis is based on four original articles published or in the process of publication, which form the basis of the following three chapters. In the first one, we analyzed four bright type 2 AGNs using Multi Unit Spectroscopic Explorer (MUSE) integral field spectroscopy, Very Large Array (VLA) and e-MERLIN radio observations with the goal of studying the interplay between radio jets, outflows, and the properties of the interstellar medium (ISM). We detected extended ionized gas outflows (up to 15 kpc, with velocities up to 1000 km/s) and identified a strong increase in the widths of emission lines perpendicular to the jets, consistent with interactions between the jets and the ISM. Even low-power jets were found to be capable of injecting significant amounts of energy into the interstellar medium. The second one focuses on the study of two Ultra Luminous InfraRed Galaxies (ULIRGs), Arp 220 and Mrk231, observed with JWST/NIRSpec. We spatially resolved the ionized and hot molecular gas in the nuclear region and identified multiple high-velocity multiphase outflows originating from both nuclei of Arp220. Combined NIRSpec and ALMA observations reveal that most of the outflowing mass resides in cold molecular gas. The multidirectional outflows in Arp 220 may affect the interstellarmedium more uniformly than the collimated outflows typically seen in isolated galaxies. In Mrk231, we performed a kinematic study of the gas in both the infrared (IR) and optical bands using MEGARA IFU data. We identified clumps at velocity up to 1000 km/s and an outflows with velocity up to 2000 km/s. Moreover, we proposed a new binary black hole model (BBH) that can potentially explain multiple multi-band observational features of Mrk231, building on the hypothesis first suggested by Yan et al. (2015). Finally, in the last chapter, we identified dual or gravitationally lensed AGNs using the first Quick Release (Q1) of Euclid data. We developed a convolutional neural network (CNN) trained on realistic simulations, capable of detecting pairs of AGNs at sub-arcsecond separations. Once we learned the potential of the CNN from simulations and its outperformance compared to standard methods, we applied this method to approximately 6,000 quasars (QSO). We estimated a fraction of dual AGNs to be approximately 0.25%, and identified promising candidates, highlighting the potential of machine learning (ML) to discover these rare systems in future Euclid image release. This thesis explored different phenomena at work in galaxies that are fundamental for understanding their evolution and for constraining models, providing new insights into the roles of these processes.