论文标题
贝叶斯证据驱动的仪器系统学诊断天空平均21厘米宇宙学实验
Bayesian evidence-driven diagnosis of instrumental systematics for sky-averaged 21-cm cosmology experiments
论文作者
论文摘要
我们证明了贝叶斯循证分析在诊断和解散仪器系统效应中的21厘米信号的有效性。作为一个案例研究，我们考虑了具有注射系统的模拟到达管道。我们证明，如果系统性保持不足，则可以实现非常差的性能或错误的信号恢复。这些效果包括相似于非常深或宽的信号的天空平均21 cm后验估计。但是，当包括系统的参数化模型时，信号恢复的性能会大大提高。最重要的是，基于贝叶斯的循证模型比较能够确定是否需要这样的系统模型，因为实验数据集的真实潜在生成模型原则上是未知的。因此，我们主张一条能够测试各种潜在系统错误的管道，贝叶斯证据充当检测其存在的机制。
We demonstrate the effectiveness of a Bayesian evidence-based analysis for diagnosing and disentangling the sky-averaged 21-cm signal from instrumental systematic effects. As a case study, we consider a simulated REACH pipeline with an injected systematic. We demonstrate that very poor performance or erroneous signal recovery is achieved if the systematic remains unmodelled. These effects include sky-averaged 21-cm posterior estimates resembling a very deep or wide signal. However, when including parameterised models of the systematic, the signal recovery is dramatically improved in performance. Most importantly, a Bayesian evidence-based model comparison is capable of determining whether or not such a systematic model is needed as the true underlying generative model of an experimental dataset is in principle unknown. We, therefore, advocate a pipeline capable of testing a variety of potential systematic errors with the Bayesian evidence acting as the mechanism for detecting their presence.
