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首页> 外文期刊>The Astrophysical journal >MAPPING THE GAS TEMPERATURE DISTRIBUTION IN EXTENDED X-RAY SOURCES AND SPECTRAL ANALYSIS IN THE CASE OF LOW STATISTICS: APPLICATION TO ASCA OBSERVATIONS OF CLUSTERS OF GALAXIES
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MAPPING THE GAS TEMPERATURE DISTRIBUTION IN EXTENDED X-RAY SOURCES AND SPECTRAL ANALYSIS IN THE CASE OF LOW STATISTICS: APPLICATION TO ASCA OBSERVATIONS OF CLUSTERS OF GALAXIES

机译：在低统计情况下映射扩展X射线源中的气体温度分布和光谱分析：在星系类群的ASCA观测中的应用

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摘要

A simple method for mapping the temperature distribution in extended sources is developed for application to ASCA observations of galaxy clusters. Unlike the conventional approach to spatially resolved spectral analysis, this method does not require nonlinear minimization and is computationally fast and stable. Therefore, it can be implemented for a large number of regions or on a fine spatial grid. Although based on a Taylor expansion over the nonlinear parameter, the method is found to be accurate in many practical situations, the relative error for the temperature estimate being less than 2%-4% when the plasma temperature exceeds ～2 keV. This method is not intended to replace conventional spectral analysis but to supplement it, providing relatively fast and easy construction of temperature maps, which may be used as a guide to further detailed analysis of particularly interesting regions using conventional spectral fitting. Conventional spectral analysis in the case of moderate and low numbers of counts is discussed. A practical recipe for unbiased parameter estimation is suggested and verified in Monte Carlo simulations for commonly used spectral models. A simple modification of the χ~2 statistic (calculation of weights based on the smoothed observed spectrum) yields nearly unbiased parameter estimates and correct confidence interval determination with no need for regrouping (binning) the energy channels even in the case of low statistics (～ 50-100 counts in the observed spectrum with several hundred channels).
机译：开发了一种用于绘制扩展源中温度分布的简单方法，以应用于ASCA对星系团的观测。与传统的空间解析光谱分析方法不同，此方法不需要非线性最小化，并且计算快速且稳定。因此，它可以在大量区域或精细的空间网格上实现。尽管基于非线性参数的泰勒展开，该方法在许多实际情况下都是准确的，当等离子体温度超过〜2 keV时，温度估算的相对误差小于2％-4％。此方法无意替代常规光谱分析，而是要对其进行补充，以提供相对快速便捷的温度图构造，该曲线图可以用作使用常规光谱拟合对特别感兴趣的区域进行进一步详细分析的指南。讨论了中等数量和低数量情况下的常规光谱分析。提出了实用的无偏参数估计方法，并在蒙特卡洛模拟中对常用的光谱模型进行了验证。对χ〜2统计量的简单修改（基于平滑观测频谱的权重计算）可产生几乎无偏差的参数估计值和正确的置信区间确定，即使在统计量较低的情况下也无需重新组合（合并）能量通道（〜在具有数百个通道的观测频谱中计数50-100）。

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