Rapid Separable Analysis of Higher Order Correlators in Large Scale Structure
J.R. Fergusson, D.M. Regan, E.P.S. Shellard

TL;DR
This paper introduces a fast, separable mode expansion method for estimating and reconstructing higher-order correlators like the bispectrum and trispectrum in large scale structure data, improving computational efficiency.
Contribution
It develops a novel, efficient separable approach for bispectrum and trispectrum analysis, reducing computational complexity and enabling nonGaussian initial condition generation in N-body simulations.
Findings
Requires only O(n_max * l_max^3) operations for bispectrum estimation
Requires only O(n_max^{4/3} * l_max^3) operations for trispectrum estimation
Provides a method for generating nonGaussian initial conditions for N-body codes
Abstract
We present an efficient separable approach to the estimation and reconstruction of the bispectrum and the trispectrum from observational (or simulated) large scale structure data. This is developed from general CMB (poly-)spectra methods which exploit the fact that the bispectrum and trispectrum in the literature can be represented by a separable mode expansion which converges rapidly (with terms). With an effective grid resolution (number of particles/grid points ), we present a bispectrum estimator which requires only operations, along with a corresponding method for direct bispectrum reconstruction. This method is extended to the trispectrum revealing an estimator which requires only operations. The complexity…
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