论文标题
使用时机的模板库改善Gstlal Inspiral管道中的背景估计技术
Improving the background estimation technique in the GstLAL inspiral pipeline with the time-reversed template bank
论文作者
论文摘要
背景估计对于确定重力波事件的统计意义很重要。当前，背景模型是使用估计技术从应变数据中构建的，这些估计技术将应变数据与任何潜在信号隔离开来。但是，随着重力波信号的观察频繁，这种绝缘的有效性将降低。当信号泄漏到背景模型中时，就会发生污染。在这项工作中，我们通过限制建模的GW波形，展示了一种改进的背景估计技术，用于从二进制中子星凝胶中搜索引力波（GWS）的背景估计技术。我们发现，新方法可以牢固地避免以每20秒约1个信号速率的信号污染，并在信号存在下保留干净的背景模型。
Background estimation is important for determining the statistical significance of a gravitational-wave event. Currently, the background model is constructed numerically from the strain data using estimation techniques that insulate the strain data from any potential signals. However, as the observation of gravitational-wave signals become frequent, the effectiveness of such insulation will decrease. Contamination occurs when signals leak into the background model. In this work, we demonstrate an improved background estimation technique for the searches of gravitational waves (GWs) from binary neutron star coalescences by time-reversing the modeled GW waveforms. We found that the new method can robustly avoid signal contamination at a signal rate of about one per 20 seconds and retain a clean background model in the presence of signals.
