I recently joined the Institute of Research and Technological Innovation at AREA Science Park in Trieste, Italy as a Data Scientist in the Laboratory of Data Engineering.

Several bright and massive galaxy candidates at high redshifts have been recently observed by the James Webb Space Telescope. Such …

In the pursuit of primordial non-Gaussianities, we hope to access smaller scales across larger comoving volumes. At low redshift, the …

Cosmologists search for answers about essential properties of the Universe on large scales, to understand its origin, evolution, and fate. In the current cosmological paradigm, the Λ Cold Dark Matter model, these properties are described by a small set of parameters determining the initial conditions for the formation of structures, the expansion rate, and the amount of matter, and radiation in the Universe. In this talk, we leverage novel developments in computational topology to build higher-order, interpretable and expressive summary statistics of galaxy redshift surveys to provide unprecedented constraints to these properties. Galaxy surveys observe angular positions and redshifts across large cosmological volumes, allowing us to trace the evolution of structures as a function of time. Standard methods exploit the measurement of the correlation of galaxy pairs as a function of distance, as theoretical and numerical predictions for this observable exist and are reliable on large scales. As experiments will observe galaxy maps over wider and wider ranges of scales and redshifts and with better and better signal-to-noise ratios, these predictions will not improve as fast. We propose to explore novel summary statistics that are better suited for the dataset we have. Persistent homology is a method for computing topological features of a map at different spatial resolutions. It is built on a mathematically well-defined framework that is optimal for extracting information from high-dimensional, incomplete, and noisy datasets, such as galaxy maps. The program establishes an analysis pipeline for current and future surveys and a framework for likelihood analysis and the production of fast simulations for results validation. The final goal is to address fundamental questions in cosmology, such as the origin of structures, the amplitude of matter fluctuations, the expansion history of the universe, and the detection of the sum of neutrino masses.