| Abstract: |
The standard model of cosmology has been remarkably successful, providing a robust framework for understanding the Universe. However, it leaves several fundamental questions unresolved. Moreover, growing tensions and anomalies in current datasets suggest the possibility of new physics beyond this paradigm. The distribution of galaxies encodes critical information about the origin and dynamics of the Universe. Ongoing and upcoming galaxy surveys offer unprecedented data volumes and number densities, opening exciting opportunities to search for tensions and anomalies. Fully exploiting this data requires advanced algorithms that go beyond the widely used 2-point statistics. In this talk, I will show how higher-order statistics can extract additional cosmological information and uncover otherwise hidden features in the data. I will further discuss how observables can be combined with simulation-based inference to enable more flexible frameworks for testing cosmological models. Finally, I will present examples of how these methods can be used to search for anomalies, including parity violation on cosmological scales, with potential implications for the matter-antimatter asymmetry and the physics of the early Universe.
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