In this work we empirically measure the detection efficiency of Kepler pipeline used to create the final Kepler Threshold Crossing Event (TCE; Twicken et al. 2016) and planet candidate catalogs (Thompson et al. 2018), a necessary ingredient for occurrence rate calculations using these lists. By injecting simulated signals into the calibrated pixel data and processing those pixels through the pipeline as normal, we quantify the detection probability of signals as a function of their signal strength and orbital period. In addition we investigate the dependence of the detection efficiency on parameters of the target stars and their location in the Kepler field of view. We find that the end-of-mission version of the Kepler pipeline returns to a high overall detection efficiency, averaging a 90-95% rate of detection for strong signals across a wide variety of parameter space. We find a weak dependence of the detection efficiency on the number of transits contributing to the signal and the orbital period of the signal, and a stronger dependence on the stellar effective temperature and correlated noise properties. We also find a weak dependence of the detection efficiency on the position within the field of view. By restricting the Kepler stellar sample to stars with well-behaved correlated noise properties, we can define a set of stars with high detection efficiency for future occurrence rate calculations.

中文翻译：

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测量开普勒管道中的传输信号恢复。四、DR25 行星候选目录的完整性

在这项工作中，我们凭经验测量了用于创建最终开普勒阈值交叉事件（TCE；Twicken 等人，2016 年）和行星候选目录（Thompson 等人，2018 年）的开普勒管道的检测效率，这是使用这些清单。通过将模拟信号注入校准的像素数据并通过管道正常处理这些像素，我们将信号的检测概率量化为信号强度和轨道周期的函数。此外，我们研究了探测效率对目标恒星参数及其在开普勒视场中的位置的依赖性。我们发现任务结束版本的开普勒管道恢复了较高的整体检测效率，在各种参数空间中对强信号的平均检测率为 90-95%。我们发现探测效率对信号和信号轨道周期有贡献的凌日次数的弱依赖性，以及对恒星有效温度和相关噪声特性的更强依赖性。我们还发现检测效率对视场内位置的依赖性很弱。通过将开普勒恒星样本限制为具有良好相关噪声特性的恒星，我们可以定义一组具有高探测效率的恒星，用于未来的出现率计算。以及对恒星有效温度和相关噪声特性的更强依赖性。我们还发现检测效率对视场内位置的依赖性很弱。通过将开普勒恒星样本限制为具有良好相关噪声特性的恒星，我们可以定义一组具有高探测效率的恒星，用于未来的出现率计算。以及对恒星有效温度和相关噪声特性的更强依赖性。我们还发现检测效率对视场内位置的依赖性很弱。通过将开普勒恒星样本限制为具有良好相关噪声特性的恒星，我们可以定义一组具有高探测效率的恒星，用于未来的出现率计算。