论文标题
丽莎恒星 - 原素黑洞合并的参数估计
Parameter Estimation for Stellar-Origin Black Hole Mergers In LISA
论文作者
论文摘要
现有地面重力波检测器检测到的恒星起源黑洞二进制（SOBHB）的种群是未来空间基于空间的激光干涉仪太空天线（LISA）的令人兴奋的目标。 LISA对频率的信号敏感，高于地面检测器。因此，SOBHB信号将在其合并之前数十年的进化中更早地检测到。然后，合并将发生在地面检测器覆盖的频带中。在合并之前观察SOBHB几年可以帮助区分这些系统的祖细胞模型。我们提出了一种新的贝叶斯参数估计算法，用于使用基于时间频率（小波）的似然函数的SOBHB的LISA观察结果。与标准频域方法相比，我们的技术通过几个数量级加速了分析，并可以有效地处理非平稳噪声。
The population of stellar origin black hole binaries (SOBHBs) detected by existing ground-based gravitational wave detectors is an exciting target for the future space-based Laser Interferometer Space Antenna (LISA). LISA is sensitive to signals at significantly lower frequencies than ground-based detectors. SOBHB signals will thus be detected much earlier in their evolution, years to decades before they merge. The mergers will then occur in the frequency band covered by ground-based detectors. Observing SOBHBs years before merger can help distinguish between progenitor models for these systems. We present a new Bayesian parameter estimation algorithm for LISA observations of SOBHBs that uses a time-frequency (wavelet) based likelihood function. Our technique accelerates the analysis by several orders of magnitude compared to the standard frequency domain approach and allows for an efficient treatment of non-stationary noise.
