Large-Scale Structure beyond the Power Spectrum

As recent and future galaxy surveys map the large-scale structure of the universe with unprecedented pace and precision, it is worthwhile to consider innovative data analysis methods beyond traditional Gaussian 2-point statistics to extract more cosmological information from those datasets. Such efforts are often plagued by substantially increased complexity of the analysis. Hoping to improve this, I will present simple, nearly optimal methods to measure 3-point statistics as easily as 2-point statistics, by cross-correlating the mass density with specific quadratic fields [arXiv:1411.6595]. Inspired by these results, I will argue that BAO reconstructions already combine 2-point statistics with certain 3- and 4-point functions automatically [arXiv:1508.06972]. I will present several new Eulerian and Lagrangian reconstruction algorithms and discuss their performance in simulations.

Speaker: Marcel Schmittfull (UC Berkeley)