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arXiv 1201.3563gr-qcastro-ph.COastro-ph.IM
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爱因斯坦引力波望远镜的模拟数据挑战

A Mock Data Challenge for the Einstein Gravitational-Wave Telescope

Tania Regimbau, Thomas Dent, Walter Del Pozzo, Stefanos Giampanis, Tjonnie G. F. Li, Craig Robinson, Chris Van Den Broeck, Duncan Meacher, Carl Rodriguez, Banga… 展开作者

Tania Regimbau, Thomas Dent, Walter Del Pozzo, Stefanos Giampanis, Tjonnie G. F. Li, Craig Robinson, Chris Van Den Broeck, Duncan Meacher, Carl Rodriguez, Bangalore S. Sathyaprakash, Katarzyna Wójcik

摘要:

爱因斯坦望远镜(Einstein Telescope,ET)是第三代引力波天文台。它的振幅灵敏度将比先进的LIGO和Virgo高出10倍,它还可以将低频灵敏度扩展到1- 3 Hz,而先进探测器的灵敏度为10- 20 Hz。这样的观测站将有可能观测各种不同的GW源,包括宇宙学距离上的紧凑双星系统。ET对双星中子星(BNS)合并的预期达到了红移$z\simeq 2$,可检测到的BNS合并的速率可能高达每几十秒或几百秒一次,每次持续数天。在ET敏感频段内,ET阳性率为100%。在这样一个信号丰富的环境中,数据分析的一个关键问题是是否可以区分重叠信号。在本文中,我们模拟的GW信号从宇宙人口的BNS和问以下问题:这个人口创造一个混乱的背景,限制ET的能力,以检测前景来源?当前算法在区分重叠BNS信号方面的效率如何?是否有可能通过将来自ET天文台不同探测器的数据互相关来辨别数据中存在的信号群?我们发现,目前用于分析LIGO和Virgo数据的算法已经足够强大,可以检测到ET中预期的来源,但需要新的算法来充分利用ET数据。

英文摘要:

Einstein Telescope (ET) is conceived to be a third generation gravitational-wave observatory. Its amplitude sensitivity would be a factor ten better than advanced LIGO and Virgo and it could also extend the low-frequency sensitivity down to 1--3 Hz, compared to the 10--20 Hz of advanced detectors. Such an observatory will have the potential to observe a variety of different GW sources, including compact binary systems at cosmological distances. ET's expected reach for binary neutron star (BNS) coalescences is out to redshift $z\simeq 2$ and the rate of detectable BNS coalescences could be as high as one every few tens or hundreds of seconds, each lasting up to several days. %in the sensitive frequency band of ET. With such a signal-rich environment, a key question in data analysis is whether overlapping signals can be discriminated. In this paper we simulate the GW signals from a cosmological population of BNS and ask the following questions: Does this population create a confusion background that limits ET's ability to detect foreground sources? How efficient are current algorithms in discriminating overlapping BNS signals? Is it possible to discern the presence of a population of signals in the data by cross-correlating data from different detectors in the ET observatory? We find that algorithms currently used to analyze LIGO and Virgo data are already powerful enough to detect the sources expected in ET, but new algorithms are required to fully exploit ET data.

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。

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