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arXiv 0908.3766gr-qc
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利用F统计模板库在模拟LISA数据中寻找银河系白矮星双星

Searching for Galactic White Dwarf Binaries in Mock LISA Data using an F-Statistic Template Bank

John T. Whelan, Reinhard Prix, Deepak Khurana

摘要:

我们描述了一个F统计搜索连续引力波从银河系白矮星双星模拟LISA数据。我们的搜索方法采用了分层模板网格为基础的参数空间的探索。在第一阶段中,使用不同的模拟激光信号组合(称为TDI变量)在搜索中识别候选源。由于每个源在其真实的“多普勒参数”(固有频率和天空位置)附近生成主要最大值以及多普勒参数空间中的F统计量的许多次要最大值,因此对多个源的搜索需要区分真实信号和与其他“更响”信号相关联的次要最大值。我们的方法通过应用重合测试来拒绝在使用三个TDI变量中的每一个的搜索中在附近的参数空间位置处未找到的候选者。对于幸存的符合测试的信号,我们执行一个完全相干的搜索在一个细化的参数网格提供一个准确的参数估计的最终候选人。经过适当调整,管道能够提取1989个真实信号,只有5个假警报。刚性绝热近似的使用允许恢复的信号参数与统计预期的误差相当,虽然仍然有一些系统的过剩相对于从高斯噪声预期的统计误差。一个实验性的迭代管道,七轮信号减法和残差的重新分析,使我们能够增加信号的数量恢复到3419与29个假警报。

英文摘要:

We describe an F-statistic search for continuous gravitational waves from galactic white-dwarf binaries in simulated LISA Data. Our search method employs a hierarchical template-grid based exploration of the parameter space. In the first stage, candidate sources are identified in searches using different simulated laser signal combinations (known as TDI variables). Since each source generates a primary maximum near its true "Doppler parameters" (intrinsic frequency and sky position) as well as numerous secondary maxima of the F-statistic in Doppler parameter space, a search for multiple sources needs to distinguish between true signals and secondary maxima associated with other, "louder" signals. Our method does this by applying a coincidence test to reject candidates which are not found at nearby parameter space positions in searches using each of the three TDI variables. For signals surviving the coincidence test, we perform a fully coherent search over a refined parameter grid to provide an accurate parameter estimation for the final candidates. Suitably tuned, the pipeline is able to extract 1989 true signals with only 5 false alarms. The use of the rigid adiabatic approximation allows recovery of signal parameters with errors comparable to statistical expectations, although there is still some systematic excess with respect to statistical errors expected from Gaussian noise. An experimental iterative pipeline with seven rounds of signal subtraction and re-analysis of the residuals allows us to increase the number of signals recovered to a total of 3419 with 29 false alarms.

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