Cosmic Microwave Background Mapmaking with a Messenger Field

Cosmic Microwave Background Mapmaking with a Messenger Field
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用信使场绘制宇宙微波背景地图

DOI:
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发表时间:
2017
期刊:
影响因子:
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通讯作者:
S. K. Næss
S. K. Næss
中科院分区:
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文献类型:
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作者:
K. Huffenberger;S. K. Næss

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我们应用信使场方法来求解宇宙微波背景(CMB)观测背景下的线性最小方差制图方程。在模拟中,该方法生成的天空图的收敛速度明显快于带有对角预处理器的共轭梯度下降算法,尽管每次迭代的计算成本相似。信使方法比共轭梯度下降更好地恢复地图中的大尺度,并产生较低的总体 χ2。在单一的笔形波束近似中,信使地图制作过程的每次迭代都会产生一个无偏差的地图,并且随着迭代的进行,迭代会变得更加优化。该方法的一个变体可以处理差分数据或执行反卷积制图。信使方法不需要预处理器,但高质量的解决方案需要冷却参数来控制收敛。我们研究了这种新方法的收敛特性,并讨论了该算法如何适用于当前和未来 CMB 实验的大数据集。
We apply a messenger field method to solve the linear minimum-variance mapmaking equation in the context of Cosmic Microwave Background (CMB) observations. In simulations, the method produces sky maps that converge significantly faster than those from a conjugate gradient descent algorithm with a diagonal preconditioner, even though the computational cost per iteration is similar. The messenger method recovers large scales in the map better than conjugate gradient descent, and yields a lower overall χ2. In the single, pencil beam approximation, each iteration of the messenger mapmaking procedure produces an unbiased map, and the iterations become more optimal as they proceed. A variant of the method can handle differential data or perform deconvolution mapmaking. The messenger method requires no preconditioner, but a high-quality solution needs a cooling parameter to control the convergence. We study the convergence properties of this new method and discuss how the algorithm is feasible for the large data sets of current and future CMB experiments.
DOI: 10.1088/0067-0049/187/1/212
发表时间: 2009-06
期刊: The Astrophysical Journal Supplement Series
影响因子: --
作者:
C. Cantalupo;J. Borrill;A. Jaffe;T. Kisner;R. Stompor
通讯作者: C. Cantalupo;J. Borrill;A. Jaffe;T. Kisner;R. Stompor