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arXiv 2409.08090astro-ph.IM
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nifty-ls:使用非均匀FFT的快速精确Lomb-Scargle周期图

nifty-ls: Fast and Accurate Lomb-Scargle Periodograms Using a Non-Uniform FFT

Lehman H. Garrison, Dan Foreman-Mackey, Yu-hsuan Shih, Alex Barnett

AI总结:

本研究推出开源软件包nifty-ls,借助finufft实现的非均匀FFT计算Lomb-Scargle周期图,相比Astropy中的传统方法速度提升数倍、精度高出多个数量级,还支持GPU加速与Astropy接口集成。

摘要:

我们推出nifty-ls,这是一款用于快速、精确计算Lomb-Scargle周期图的软件包。nifty-ls利用了Lomb-Scargle周期图可通过非均匀FFT(NUFFT)计算的特性,我们采用Flatiron研究所的NUFFT软件包(finufft)来实现该计算。与Astropy中实现的Press & Rybicki (1989)方法相比,该方法实现了数倍的速度提升,同时精度高出多个数量级。nifty-ls还支持通过CUDA在GPU上进行快速计算,并与Astropy的Lomb-Scargle接口相集成。nifty-ls作为开源软件公开可用。

英文摘要:

We present nifty-ls, a software package for fast and accurate evaluation of the Lomb-Scargle periodogram. nifty-ls leverages the fact that Lomb-Scargle can be computed using a non-uniform FFT (NUFFT), which we evaluate with the Flatiron Institute NUFFT package (finufft). This approach achieves a many-fold speedup over the Press & Rybicki (1989) method as implemented in Astropy and is simultaneously many orders of magnitude more accurate. nifty-ls also supports fast evaluation on GPUs via CUDA and integrates with the Astropy Lomb-Scargle interface. nifty-ls is publicly available as open-source software.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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