Life is physics and chemistry in action. While molecular simulations of systems as complex as whole cells are now within reach, predicting chemical reactivity on relevant time and length scales remains a challenge. I will present our recent work towards bringing action – here: chemistry – to classical simulations and molecular design through machine learning. Among others, we substitute costly quantum mechanical calculations with a graph neural network-based emulator. Our framework can deal with the plethora of life’s chemistry amidst the ‘jiggling and wiggling’ of biomolecules. Importantly, we also uncover unexpected biomolecular processes that we in turn put to test in experiments. Finally, I will demonstrate how we harness a flow-matching model to predict biomolecular dynamics. Our method paves the way for generating novel flexible and functional proteins.

Top-quark pair production in association with a jet is a key process at the LHC. Its high sensitivity to the top mass and the increasing experimental precision call for the QCD corrections to be computed at the next-to-next-to-leading order (NNLO). In this seminar, I will present the computation of the two-loop Feynman integrals required to obtain NNLO QCD predictions in the leading colour approximation. These integrals are characterised by significant algebraic complexity—stemming from the multi-scale, five-particle kinematics—as well as analytic complexity, due to the appearance of nested square roots and elliptic functions. I will discuss modern methods for tackling multi-scale integrals in a way that is suitable for phenomenology, and outline first steps to extend these techniques to cases involving elliptic functions.

Quantum field theory (QFT), a framework that combines special relativity and quantum mechanics, is the language used to describe the fundamental particles and interactions of our universe. One of the most powerful tools in QFT is perturbation theory, which has given rise to some of the most precise predictions in science. There are QFTs, however, where perturbation theory does not work, the most prominent being the theory of the strong force, Quantum Chromodynamics. In this talk, I will describe some recently developed tools used to better understand non-perturbative QFTs. One of these tools is called supersymmetry, which allows one to treat the spherical cow of QFTs. Finally, I will explore whether these tools could be applicable to the real world strong force.