模拟QSO光变曲线中周期变化的检测
Detection of Periodic Variability in Simulated QSO Light Curves
摘要：
对于某些双黑洞系统，预测的周期性光变曲线行为可能在大样本中被检测到，例如大型综合巡天望远镜（LSST）预期的数百万个类星体样本。研究了在阻尼随机游走（DRW）模型模拟的光变曲线中发现周期信号的虚警概率。这个模型提供了一个很好的描述所观察到的光变曲线，并不包括周期性的行为。我们使用Lomb-Scargle周期图在一百万个模拟光变曲线中搜索周期信号，这些光变曲线正确地对DRW参数空间和LSST节奏空间进行采样。我们发现，即使是一个非常保守的阈值的虚警概率仍然产生数千个“好”的二元黑洞候选者。我们的结论是，未来声称的二元黑洞的基础上LSST光变曲线的Lomb-Scargle分析将不得不谨慎解释。
英文摘要：
Periodic light curve behavior predicted for some binary black hole systems might be detected in large samples, such as the multi-million quasar sample expected from the Large Synoptic Survey Telescope (LSST). We investigate the false-alarm probability for the discovery of a periodic signal in light curves simulated using damped random walk (DRW) model. This model provides a good description of observed light curves, and does not include periodic behavior. We used the Lomb-Scargle periodogram to search for a periodic signal in a million simulated light curves that properly sample the DRW parameter space, and the LSST cadence space. We find that even a very conservative threshold for the false-alarm probability still yields thousands of "good" binary black hole candidates. We conclude that the future claims for binary black holes based on Lomb-Scargle analysis of LSST light curves will have to be interpreted with caution.
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。
