http://arxiv.org/abs/1903.09715
As we move towards future galaxy surveys, the three point statistics will be increasingly leveraged to enhance the constraining power of the data on cosmological parameters. An essential part of the three point function estimation is performing triplet counts of synthetic data points in random catalogues. Since triplet counting algorithms scale at best as $\mathcal{O}(N^2\log N)$ with the number of particles and the random catalogues are typically at least 50 times denser than the data, this tends to be by far the most time consuming part of the measurements. Here we present a simple method of computing the necessary triplet counts involving uniform random distributions by means of simple one dimensional integrals. This speeds up the computation of the three point function by orders of magnitude, eliminating the need for random catalogues, with the triplet — and pair — counting of the data points alone being sufficient.
D. Pearson and L. Samushia
Tue, 26 Mar 19
20/72
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