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arXiv 0704.0048gr-qcastro-ph
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利用第一轮模拟LISA数据集推断白矮星双星系统

Inference on white dwarf binary systems using the first round Mock LISA Data Challenges data sets

Alexander Stroeer, John Veitch, Christian Roever, Ed Bloomer, James Clark, Nelson Christensen, Martin Hendry, Chris Messenger, Renate Meyer, Matthew Pitkin, Jen… 展开作者

Alexander Stroeer, John Veitch, Christian Roever, Ed Bloomer, James Clark, Nelson Christensen, Martin Hendry, Chris Messenger, Renate Meyer, Matthew Pitkin, Jennifer Toher, Richard Umstaetter, Alberto Vecchio, Graham Woan

摘要:

我们报告的分析选定的单源数据集从第一轮的模拟LISA数据挑战(MLDC)的白矮星二进制。我们实现了一个端到端的管道,包括一个基于网格的相干预处理单元的信号检测,和一个自动马尔可夫链蒙特卡罗后处理单元的信号评估。我们证明,我们的相干方法的信号检测是安全和准确的,并增加了准确性,并补充了额外的信息,我们的马尔可夫链蒙特卡罗方法的信号参数。我们还表明,马尔可夫链蒙特卡罗例程是另外能够准确地确定在感兴趣的频率窗口中的噪声水平。

英文摘要:

We report on the analysis of selected single source data sets from the first round of the Mock LISA Data Challenges (MLDC) for white dwarf binaries. We implemented an end-to-end pipeline consisting of a grid-based coherent pre-processing unit for signal detection, and an automatic Markov Chain Monte Carlo post-processing unit for signal evaluation. We demonstrate that signal detection with our coherent approach is secure and accurate, and is increased in accuracy and supplemented with additional information on the signal parameters by our Markov Chain Monte Carlo approach. We also demonstrate that the Markov Chain Monte Carlo routine is additionally able to determine accurately the noise level in the frequency window of interest.

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