0


未来暗能量探测器及其对系统学的鲁棒性

Future dark energy probes and their robustness to systematics
课程网址: http://videolectures.net/nipsworkshops2011_march_energy/  
主讲教师: Marisa Cristina March
开课单位: 苏塞克斯大学
开课时间: 2012-06-23
课程语种: 英语
中文简介:
我们扩展了通常用于量化未来暗能量探测器的统计性能的价值数形式,以评估未来任务对合理的系统偏差的鲁棒性。我们引入了一种新的鲁棒性优值系数,它可以在给定可观测量的任意系统偏差的情况下用Fisher矩阵形式计算。我们认为,对系统学的稳健性是一个重要的新量,在优化未来的调查时应加以考虑。我们用玩具例子来说明我们的形式主义,并将其应用于未来的Ia型超新星(SNIa)和重子声波振荡(BAO)测量。对于我们所考虑的简化的系统偏差,我们发现SNIa是一个比BAO更稳健的暗能量参数探测器。在暗能量的统计方向上,我们与暗能量的方向一致。
课程简介: We extend the Figure of Merit formalism usually adopted to quantify the statistical performance of future dark energy probes to assess the robustness of a future mission to plausible systematic bias. We introduce a new robustness Figure of Merit which can be computed in the Fisher Matrix formalism given arbitrary systematic biases in the observable quantities. We argue that robustness to systematics is an important new quantity that should be taken into account when optimizing future surveys. We illustrate our formalism with toy examples, and apply it to future type Ia supernova (SNIa) and baryonic acoustic oscillation (BAO) surveys. For the simplified systematic biases that we consider, we find that SNIa are a somewhat more robust probe of dark energy parameters than the BAO. We trace this back to a geometrical alignement of systematic bias direction with statistical degeneracy directions in the dark energy parameter space.
关 键 词: 暗能量; 鲁棒性; 声波振荡测量
课程来源: 视频讲座网
数据采集: 2020-11-30:yxd
最后编审: 2020-11-30:yxd
阅读次数: 55