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• W2940888575 abstract "Nonlinearities in the gravitational evolution, galaxy bias, and redshift-space distortion drive the observed galaxy density fields away from the initial near-Gaussian states. Exploiting such a non-Gaussian galaxy density field requires measuring higher-order correlation functions, or, its Fourier counterpart, polyspectra. Here, we present an efficient parallel algorithm for estimating higher-order polyspectra. Based upon the Scoccimarro estimator, the estimator avoids direct sampling of polygons by using the Fast-Fourier Transform (FFT), and the parallelization overcomes the large memory requirement of the original estimator. In particular, we design the memory layout to minimize the inter-CPU communications, which excels in the code performance." @default.
• W2940888575 created "2019-05-03" @default.
• W2940888575 creator A5013821884 @default.
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• W2940888575 date "2019-08-20" @default.
• W2940888575 modified "2023-10-14" @default.
• W2940888575 title "Efficient Parallel Algorithm for Estimating Higher-order Polyspectra" @default.
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• W2940888575 doi "https://doi.org/10.3847/1538-3881/ab3223" @default.
• W2940888575 hasPublicationYear "2019" @default.
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