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Parameter estimation for signals from compact binary inspirals injected into LIGO data

机译:注入LIGO数据的紧凑型二元吸气管的信号参数估计

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During the fifth science run of the Laser Interferometer Gravitational-WaveObservatory (LIGO), signals modelling the gravitational waves emitted bycoalescing non-spinning compact-object binaries were injected into the LIGOdata stream. We analysed the data segments into which such injections weremade using a Bayesian approach, implemented as a Markov-chain Monte Carlotechnique in our code SPINSPIRAL. This technique enables us to determinethe physical parameters of such a binary inspiral, including masses and spin,following a possible detection trigger. For the first time, we publish the resultsof a realistic parameter-estimation analysis of waveforms embedded in realdetector noise. We used both spinning and non-spinning waveform templatesfor the data analysis and demonstrate that the intrinsic source parameters can beestimated with an accuracy of better than 1-3% in the chirp mass and 0.02-0.05(8-20%) in the symmetric mass ratio if non-spinning waveforms are used. Wealso find a bias between the injected and recovered parameters, and attributeit to the difference in the post-Newtonian orders of the waveforms used forinjection and analysis.
机译:在激光干涉仪重力波观测站(LIGO)的第五次科学运行期间,将通过模拟非旋转紧凑对象二进制二进制文件发出的引力波建模的信号注入了LIGOdata流。我们分析了使用贝叶斯方法进行注入的数据段,该贝叶斯方法在我们的代码SPINSPIRAL中实现为马尔可夫链蒙特卡洛技术。这项技术使我们能够在可能的检测触发条件之后确定这种二进制吸气体的物理参数,包括质量和自旋。首次,我们发布了对真实检测器噪声中嵌入的波形进行实际参数估计分析的结果。我们使用旋转和非旋转波形模板进行数据分析,并证明可以以the质量的1-3%和对称质量的0.02-0.05(8-20%)的精度估算固有源参数。如果使用非旋转波形,则为比率。我们还发现注入和恢复的参数之间存在偏差,并且归因于用于注入和分析的波形在牛顿后阶数上的差异。

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