论文标题

重力波检测器网络的自我校准

Self-calibration of Networks of Gravitational Wave Detectors

论文作者

Schutz, B. F., Sathyaprakash, B. S.

论文摘要

随着Ligo和处女座的升级,改进的校准系统可以与预期的信号到噪声增强保持同步。我们在这里探索了一种使用天文信号的校准方法,即紧凑型对象二进制文件的灵感信号,我们表明它可以原则上可以在未来重力波科学所需的sub-1 \%精度水平上进行校准。我们展示了这些瞬态事件的集合如何用于测量三种或更敏感仪器的网络中单个检测器的校准误差。与望远镜一样,使用检测到的事件对重力波检测器进行相对校准比绝对校准更容易实现,而原则上仍需要使用硬件方法来进行至少一个检测器以一个频率进行。我们提出的方法使用所谓的无效流流,这是任何具有三个或更多不同定向检测器的网络中存在的检测器输出的无信号线性组合。如果检测器输出中的信号幅度忠实于真实信号,则信号不会出现在空流中。频率依赖性的校准误差以及检测器之间的相对校准和定时误差使残留在空流中。每个检测器的残差量取决于源方向。我们将匹配过滤的方法调整为从该残差中提取每个检测器的校准误差的问题。这需要线性地组合足够数量的检测信号的过滤器输出,并且原则上可以在足够长的观察过程中实现任何所需的准确性。我们预计,预期在5年内的+检测器网络可以使用这种方法来检查预期的硬件校准精度。

As LIGO and Virgo are upgraded, improving calibration systems to keep pace with the anticipated signal-to-noise enhancements will be challenging. We explore here a calibration method that uses astronomical signals, namely inspiral signals from compact-object binaries, and we show that it can in principle enable calibration at the sub-1\% accuracy levels needed for future gravitational wave science. We show how ensembles of these transient events can be used to measure the calibration errors of individual detectors in a network of three or more comparably sensitive instruments. As with telescopes, relative calibration of gravitational-wave detectors using detected events is easier to achieve than absolute calibration, which in principle would still need to be done with a hardware method for at least one detector at one frequency. Our proposed method uses the so-called null streams, the signal-free linear combinations of the outputs of the detectors that exist in any network with three or more differently oriented detectors. Signals do not appear in the null stream if the signal amplitude in the detector output is faithful to that of the real signal. Frequency-dependent calibration errors and relative calibration and timing errors between detectors leave a residual in the null stream. The amount of residual from each detector depends on the source direction. We adapt the method of matched filtering to the problem of extracting the calibration error of each detector from this residual. This requires combining linearly the filter outputs of a sufficient number of detected signals, and in principle it can achieve any desired accuracy in a long enough observation run. We anticipate that A+ detector networks, expected in 5 years, could employ this method to check anticipated hardware calibration accuracies.

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