In Search of The Building Blocks of the Universe

We live in an exceptional era of precision cosmology, marked by rapidly advancing observational probes that explore the Universe across many length scales. While these experiments offer clues about the geometry, dynamics, and large-scale structure of the cosmos, they still leave the origin and much of the evolution and structure of the Universe unknown. One of the key steps to answer these questions is to uncover the building blocks of theoretical models in both linear and non-linear regimes.

In this talk, I will present methods for uncovering physical degrees of freedom, outlining the standard approaches and presenting an alternative, simple and straightforward way. I will then show how one can naturally connect this approach to machine learning. Finally, I will introduce the framework of constrained gravity, and discuss how such approaches can help address long-standing challenges in fundamental physics and open new directions across disciplines.