KIPAC Tea: Constraining Cosmology with Strong Gravitational Lensing and Stellar Kinematics / Galaxy Clustering Beyond Two-Point Statistics

Galaxy Clustering Beyond Two-Point Statistics - Elisabeth Krause (Univ. of Arizona)

The last few years has seen the emergence of a vast array of novel techniques for the analysis of high precision data from upcoming galaxy surveys, which are primarily motivated by the notion that any optimal analysis of galaxy clustering data should extend beyond the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge ``Beyond-2pt’’. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, field-level effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference.

I will review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches.