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arXiv 1405.0482astro-ph.IM
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下一代地基亚毫米波仪器的制图

Map-making for the Next Generation of Ground-based Submillimeter Instruments

Gaelen Marsden, Adam Brazier, Tim Jenness, Jack Sayers, Douglas Scott

摘要:

目前的地面亚毫米仪器(如SCUBA-2、SHARC-2和LABOCA)有数百至数千个探测器,以数十至数百赫兹采样,每晚产生高达数百千兆字节的数据。由于大气信号和温度振荡,噪声在探测器之间和时间上是相关的,因此简单的制图是不适用的。此外,数据集的大小使得直接基于似然的反演技术难以处理。因此,目前大多数亚毫米相机的数据处理方法是采用迭代方法,以分离噪声和天空信号,从而有效地产生天文图像。我们研究了今天的地图制作者如何扩展到下一代仪器,这将有成千上万的探测器以数千赫兹采样,从而产生具有挑战性的数据集。我们提出了减少这种大数据集的策略。

英文摘要:

Current ground-based submillimeter instruments (e.g. SCUBA-2, SHARC-2 and LABOCA) have hundreds to thousands of detectors, sampled at tens to hundreds of hertz, generating up to hundreds of gigabytes per night. Since noise is correlated between detectors and in time, due to atmospheric signals and temperature oscillations, naive map-making is not applicable. In addition, the size of the data sets makes direct likelihood based inversion techniques intractable. As a result, the data reduction approach for most current submm cameras is to adopt iterative methods in order to separate noise from sky signal, and hence effectively produce astronomical images. We investigate how today's map-makers scale to the next generation of instruments, which will have tens of thousands of detectors sampled at thousands of hertz, leading to data sets of challenging size. We propose strategies for reducing such large data sets.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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