The early fluctuations in the Universe play a crucial role in the success of the ΛCDM (Lambda Cold Dark Matter) model, which helps explain the Universe as we see it today. In the simplest models of inflation, these initial fluctuations are Gaussian, and measurements of the Cosmic Microwave Background (CMB) by the Planck satellite have constrained any deviations from this Gaussian pattern to a precision of one part in ten thousand. Detecting deviations from this pattern, known as Primordial Non-Gaussianities (PNG), would provide new insights into the nature of inflation. However, according to current theory, PNG are expected to be even smaller than what Planck has detected so far.
A promising alternative for detecting PNG is the large-scale structure (LSS) of the Universe, which involves studying the distribution of galaxies. In my research, I study the three-dimensional clustering of quasars from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16) (https://arxiv.org/abs/2309.15814). Using optimal quadratic estimators, I improved constraints on local PNG by about 30% compared to standard techniques. This work highlights the importance of using state-of-the-art algorithms for analyzing data from next-generation spectroscopic surveys, such as the ESA Euclid satellite and the Dark Energy Spectroscopic Instrument (DESI).
