A new fast parallel statistical measurement technique for computational cosmology

R. Thacker, H. Couchman
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引用次数: 6

Abstract

Higher order cumulants of point processes require significant computational effort to calculate, particularly when evaluated using standard methods such as counts-in-cells. While newer techniques based on tree algorithms are more efficient, they still suffer from shot noise problems in homogeneous systems. We present a new algorithm for calculating higher order moments using Fourier methods. A filtering technique is used to suppress noise, and this approach allows us to calculate skew and kurtosis even when the point process is highly homogeneous. The algorithm can be implemented efficiently in a shared memory parallel environment provided a data-local random sampling technique is used.
一种新的计算宇宙学快速并行统计测量技术
点过程的高阶累积量需要大量的计算工作来计算,特别是当使用诸如计数单元等标准方法进行评估时。虽然基于树算法的新技术更有效,但它们在同质系统中仍然存在散点噪声问题。提出了一种利用傅里叶方法计算高阶矩的新算法。使用滤波技术来抑制噪声,这种方法允许我们在点过程高度均匀的情况下计算偏度和峰度。如果采用数据局部随机抽样技术,该算法可以在共享内存并行环境下高效实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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