Recent astronomical observations have revealed that magnetic fields permeate not only galaxies and clusters, but also the voids and filaments of the cosmic web. The origin of these large-scale magnetic fields remains an open problem, but comparisons with cosmological MHD simulations favour scenarios in which these magnetic fields were produced in the very early Universe. If confirmed, such primordial magnetic fields would offer a unique observational probe of the first microseconds after the Big Bang, potentially connected to physics beyond the Standard Model.

Extracting reliable information from collider data requires a combination of mathematical, computational and statistical tools to model the observed distributions, often with the help of powerful simulations. But when simulations cannot be fully trusted, data-driven approaches become indispensable. In this talk, I will present probabilistic and Bayesian tools that provide a flexible, data-driven method for unsupervised training on probabilistic models of collider observables, highlighting their advantages for parameter inference and uncertainty estimation.

In the first of the talk I will discuss the phenomenology of cosmic-ray diffusion in the Galaxy and the associated gamma-ray and neutrino emission. The aim is to understand how the combined study of local cosmic-ray spectra and diffuse emissions can help to unveil anomalies that may point towards either non-standard propagation scenarios (and new astrophysical phenomena in general), or new physics (for instance, particle dark matter annihilation/decay).

Since the discovery of the Higgs at the LHC, particle physics model building has been confronted with a severe conceptual challenge: the inferred values of the Higgs’ mass and self-coupling both appear to be fine-tuned. This not only poses the question what kind of new physics could explain such a behavior, but also undermines phenomenological efforts as acknowledging the possibility of fine-tuning oftentimes allows for the evasion of any experimental constraints. In the first half of my talk, I will review these fine-tunings and their implications more generally.

Active galactic nuclei (AGN) drive powerful, multiphase outflows into their host galaxies which are expected to play a key role in galaxy evolution. However, exactly how small-scale accretion disc winds couple to the ISM to drive these outflows remains an open question. In this talk, I will discuss our AGN in Clumpy DisCs (ACDC) simulations which feature a physically-motivated AGN wind model embedded in an idealised galaxy disc with a resolved ISM, manually distributed in a clumpy substructure.