Updating the WFC3/UVIS CTE Model and Mitigation Strategies
Updating the WFC3/UVIS CTE Model and Mitigation Strategies
复制标题
更新 WFC3/UVIS CTE 模型和缓解策略
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Ben Kuhn June
中科院分区：
文献类型：
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作者：
Jay Anderson;S. Baggett;Ben Kuhn June
WFC3/UVIS基于像素的电荷转移效率（CTE）校正最后一次更新是在2016年。由于CTE的强度通常随时间线性增加，暖像元的数量也是如此，在HST操作5年后，效果几乎是原来的两倍，并且有两倍的暖像元可用来进行校正。不幸的是，新模型证实，自安装WFC3/UVIS以来，电荷转移损失继续稳步增加。现在，即使在20个电子的背景下，靠近芯片间隙的源（即经历最大并行传输次数的源）的CTE损耗几乎为50%，而2016年约为30%。基于像素的算法只有在校正小到足以被认为是对接收信号的扰动时才能很好地工作。如果校正量过大，则算法容易放大噪声，对图像弊大于利。出于这个原因，默认的管道设置现在被设计为抑制微弱源的校正，以避免噪声放大。一般来说，对于在每像素至少20的图像背景下具有相对明亮目标（S/N b> ~30）的观测者，新的基于像素的CTE校正效果很好，校正目标在5%以内。对于目标较弱的观测者，新算法将对其进行最小化处理，以避免噪声放大，因此需要进行额外的调整。我们向用户提供关于如何规划观测以及如何减少观测以最大限度地利用WFC3/UVIS观测的建议。未来的ISR将提供更详细的处方，说明如何校正明亮和暗淡的光源。
The pixel-based charge transfer efficiency (CTE) correction was last updated for WFC3/UVIS in 2016. Since the strength of CTE generally increases linearly with time, as does the population of warm pixels, the effect is almost twice as strong after five additional years of HST operations, and there are twice as many warm pixels available to use in deriving the correction. Unfortunately, the new model confirms that charge-transfer losses have continued to increase steadily since WFC3/UVIS was installed. Now, even with a background of 20 electrons, CTE losses are almost 50% for sources near the chip-gap (i.e., sources that undergo the maximum number of parallel transfers), compared to about 30% in 2016. The pixel-based algorithm works well only when the correction is small enough to be considered a perturbation on the signal received. If the correction is too large, then the algorithm tends to amplify noise, which causes more harm to the image than benefit. For this reason, the default pipeline setting is now designed to suppress the correction for faint sources in order to avoid noise amplification. In general, for observers with relatively bright targets (S/N > ~30) on image backgrounds of at least 20 eper pixel, the new pixel-based CTE correction works well, correcting targets to within 5%. Observers with fainter targets, which the new algorithm treats minimally in order to avoid noise amplification, will need to make additional adjustments. We provide advice to users about how to plan observations and how to carry out reductions in order to get the most out of WFC3/UVIS observations. A future ISR will provide more detailed prescriptions on how to correct sources bright and faint.