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未来的暗能量探测及其鲁棒性研究

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: 萨塞克斯大学
开课时间: 2012-01-23
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优点形式主义图,以评估未来任务对可信系统偏差的稳健性。我们引入了一个新的优点稳健性图,该图可以在Fisher矩阵形式中计算,给出了可观测量中任意系统偏差。我们认为,对系统学的鲁棒性是一个重要的新数量,应考虑到优化未来的调查。我们用玩具例子说明了我们的形式主义,并将其应用于未来的IA超新星(SNIA)和重子声学振荡(BAO)测量。对于我们考虑的简化的系统偏差,我们发现snia比bao更能探测暗能量参数。我们将其追溯到暗能量参数空间中系统偏压方向与统计简并方向的几何对准。
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: 鲁棒性; 矩阵形式主义; 系统偏差; 暗能量参数空间
课程来源: 视频讲座网
最后编审: 2020-06-02:毛岱琦(课程编辑志愿者)
阅读次数: 38