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Clipping the Cosmos: The Bias and Bispectrum of Large Scale Structure
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A large fraction of the information collected by cosmological surveys is simply discarded to avoid lengthscales which are difficult to model theoretically. We introduce a new technique which enables the extraction of useful information from the bispectrum of galaxies well beyond the conventional limits of perturbation theory. Our results strongly suggest that this method increases the range of scales where the relation between the bispectrum and power spectrum in tree-level perturbation theory may be applied, from k_max ~ 0.1 h/Mpc to ~ 0.7 h/Mpc. This leads to correspondingly large improvements in the determination of galaxy bias. Since the clipped matter power spectrum closely follows the linear power spectrum, there is the potential to use this technique to probe the growth rate of linear perturbations and confront theories of modified gravity with observation.
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Hermes - Towards an Optimal High-Performance Algorithm for Cosmic Statistics of Large Data Sets
Hermes/PyHermes reconstructs catalogues in a scaling-function basis and unifies CIC, 2PCF, 3PCF, marked, and operator-based cosmic statistics as reusable window operations with FFT/MPI/GPU scaling.
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