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arXiv 1502.04370gr-qc
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一种快速并行估计致密双星聚结引力波参数的新方案

A novel scheme for rapid parallel parameter estimation of gravitational waves from compact binary coalescences

C. Pankow, P. Brady, E. Ochsner, R. O'Shaughnessy

摘要:

我们介绍了一个高度并行化的架构,用于估计参数的紧凑的二进制合并使用引力波数据和波形模型。使用球面谐波模式分解,波形被表示为取决于固有参数(例如质量)的模式的总和,其中系数取决于观察者依赖的外部参数(例如距离、天空位置)。然后对这些模式的数据进行预过滤,在固定的固有参数,使有效地评估通用源位置和方向的可能性,独立于波形长度或生成时间。我们有效地并行化我们的内在空间计算,通过整合所有外部参数,使用Monte Carlo积分策略。由于波形生成和预滤波只发生一次,因此积分成本在整个过程中占主导地位。此外,我们操作分层,使用现有的引力波搜索的信息,以确定参数空间的区域,强调在我们的采样。作为概念的证明和结果的验证,我们使用标准的时域波形实现了该算法,在最近的计算硬件上在不到一个小时的时间内处理每个事件。对于大多数事件,我们评估边缘化的可能性(证据),统计误差小于约5%,在许多情况下甚至更小。由于运行时间有限,与波形模型的起始频率无关,因此几乎不变的策略可以估计2018年高级LIGO时代的NS-NS参数。我们的算法可用于任何质量的任何噪声曲线和现有的时域模型,包括一些计算成本很高的波形。

英文摘要:

We introduce a highly-parallelizable architecture for estimating parameters of compact binary coalescence using gravitational-wave data and waveform models. Using a spherical harmonic mode decomposition, the waveform is expressed as a sum over modes that depend on the intrinsic parameters (e.g. masses) with coefficients that depend on the observer dependent extrinsic parameters (e.g. distance, sky position). The data is then prefiltered against those modes, at fixed intrinsic parameters, enabling efficiently evaluation of the likelihood for generic source positions and orientations, independent of waveform length or generation time. We efficiently parallelize our intrinsic space calculation by integrating over all extrinsic parameters using a Monte Carlo integration strategy. Since the waveform generation and prefiltering happens only once, the cost of integration dominates the procedure. Also, we operate hierarchically, using information from existing gravitational-wave searches to identify the regions of parameter space to emphasize in our sampling. As proof of concept and verification of the result, we have implemented this algorithm using standard time-domain waveforms, processing each event in less than one hour on recent computing hardware. For most events we evaluate the marginalized likelihood (evidence) with statistical errors of less than about 5%, and even smaller in many cases. With a bounded runtime independent of the waveform model starting frequency, a nearly-unchanged strategy could estimate NS-NS parameters in the 2018 advanced LIGO era. Our algorithm is usable with any noise curve and existing time-domain model at any mass, including some waveforms which are computationally costly to evolve.

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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