arXiv 1010.16412010-10-08gr-qc

数据间隙对LISA星系双星参数估计的影响

The Effect of Data Gaps on LISA Galactic Binary Parameter Estimation

Jérôme Carré, Edward K. Porter

备注：: Submitted to Classical Quantum Gravity, 11 pages, four figures

摘要：

在过去的几年里，人们在利用空间引力波探测器LISA对不同源的参数估计研究方面做出了巨大的努力。虽然这些研究调查了不同复杂性的来源，但它们都有一个共同点，那就是它们假设连续的数据流。实际上，激光干涉仪数据流将包含可能发生的事件的间隙，例如卫星天线的重新指向、卫星上积聚的静电荷的释放、微流星撞击造成的中断。在这项工作中，我们进行了大规模的Monte Carlo参数估计模拟银河双星假设数据流包含差距。由于目前尚不清楚间隙的预期持续时间和频率，我们决定将重点放在大约一小时的间隙上，每天一次或每周一次。我们还研究的情况下，以及预期的周期性差距，我们有一个连续一周的数据辍学。我们的研究结果表明，对于银河双星，每周一次的间隙引入了0.5%和1%之间的参数估计的偏差，最重要的参数，如天空的位置，振幅和频率。对于一天一个缺口的情况，这个数字上升到3%到7%之间，当我们有一天一个缺口和一周的虚假缺口时，这个数字上升到4%到9%之间。未来的研究将调查数据差距对超大质量黑洞双星和极端质量比的影响。

英文摘要：

In the last few years there has been an enormous effort in parameter estimation studies for different sources with the space based gravitational wave detector, LISA. While these studies have investigated sources of differing complexity, the one thing they all have in common is they assume continuous data streams. In reality, the LISA data stream will contain gaps from such possible events such as repointing of the satellite antennae, to discharging static charge build up on the satellites, to disruptions due to micro-meteor strikes. In this work we conduct a large scale Monte Carlo parameter estimation simulation for galactic binaries assuming data streams containing gaps. As the expected duration and frequency of the gaps are currently unknown, we have decided to focus on gaps of approximately one hour, occurring either once per day or once per week. We also study the case where, as well as the expected periodic gaps, we have a data drop-out of one continuous week. Our results show that for for galactic binaries, a gap of once per week introduces a bias of between 0.5% and 1% in the estimation of parameters, for the most important parameters such as the sky position, amplitude and frequency. This number rises to between 3% and 7% for the case of one gap a day, and to between 4% and 9% when we have one gap a day and a spurious gap of a week. A future study will investigate the effect of data gaps on supermassive black hole binaries and extreme mass ratio inspirals.

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。

摘要：

英文摘要：

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