标题： LISA数据中极端质量比旋入的检测算法 显示英文标题

标题： An algorithm for detection of extreme mass ratio inspirals in LISA data

摘要： 从一个致密天体螺旋向一个大质量黑洞（MBH）运动产生的引力波信号被认为是LISA数据流中最难检测的源之一。 由于可能信号的参数空间很大，且在LISA的灵敏度频段内经历了许多轨道周期，之前估计需要大约10^{35}个模板才能进行完全相干的搜索，这在计算上是不可行的。 这里我们描述了一种基于约束Metropolis-Hastings随机搜索的算法，该算法使我们能够在高斯仪器噪声中找到并准确估计孤立EMRI信号的参数。 我们通过Mock LISA Data Challenge第1B轮数据集的搜索结果来展示该算法的有效性。 显示英文摘要

摘要： The gravitational wave signal from a compact object spiralling toward a massive black hole (MBH) is thought to be one of the most difficult sources to detect in the LISA data stream. Due to the large parameter space of possible signals and many orbital cycles spent in the sensitivity band of LISA, it has been estimated previously that of the order of 10^{35} templates would be required for a fully coherent search with a template grid, which is computationally impossible. Here we describe an algorithm based on a constrained Metropolis-Hastings stochastic search which allows us to find and accurately estimate parameters of isolated EMRI signals buried in Gaussian instrumental noise. We illustrate the effectiveness of the algorithm with results from searches of the Mock LISA Data Challenge round 1B data sets.