Beyond-Gaussian Statistics for Cosmological Clustering - K-Nearest Neighbor by Arka Banerjee

Explore beyond-Gaussian statistics for cosmological clustering in this 34-minute conference talk by Arka Banerjee from the International Centre for Theoretical Sciences. Delve into the application of k-Nearest Neighbor techniques to analyze large-scale structure data from cosmic surveys. Learn about advanced statistical methods used to extract information from galaxy clustering patterns and their implications for our understanding of the Universe's evolution. Gain insights into how these techniques contribute to the field of precision cosmology and complement data from Cosmic Microwave Background observations. Understand the importance of such analytical approaches in interpreting data from ongoing and future large-scale structure surveys like DES, DESI, and LSST.