Recent Developments in Clustering Analysis of Large-Scale Structure

Abstract: Large-scale structure provides insights into the Universe’s expansion history and the growth rate of structure. While the 2-point statistics can capture all information in a Gaussian random field, higher-order statistics encode crucial information about gravitationally-induced nonlinearity and deviation from a Gaussian initial condition. Higher-order N-point correlation function or polyspectra as its Fourier counterpart thus allow us more precise knowledge about the energy density content of the Universe and provides unique windows into the primordial Universe. Recently, we showed that higher-order statistics could be used to test parity violation at cosmological scales. In this talk, I will present our analysis and the implication of the measurement. Finally, I will also present our recent analysis of the galaxy skew spectra as a compressed bispectrum estimator and a forecast of its cosmological information.