论文标题

JWST噪声局I:JWST NIRCAM时间序列中的随机错误来源

JWST Noise Floor I: Random Error Sources in JWST NIRCam Time Series

论文作者

Schlawin, Everett, Leisenring, Jarron, Misselt, Karl, Greene, Thomas P., McElwain, Michael W., Beatty, Thomas, Rieke, Marcia

论文摘要

JWST的传播和发射光谱将为包括生物签名的可能的生物签名提供宝贵的传播系外行星大气。然而,JWST的这项有希望的科学将需要精确的精确性和对系统错误的理解,这可能会影响宿主明星前后的行星的时间序列。在这里,我们提供了影响JWST NIRCAM时间序列数据数据的随机噪声源的估计值。我们发现,1/F噪声可以限制2组的Grism时间序列的精度(根据提取方法和提取参数,230 ppm至1000 ppm),但会像N帧/读取的平方根一样平均向下。当前的Nircam Grism时间序列模式特别受1/F噪声的影响,因为其Grismr分散方向与检测器快速阅读方向平行,但可以在Grismc方向上缓解。应注意将尽可能多的框架包括在访问中,以减少此1/F噪声源:因此,我们建议最小的检测器子阵列大小,一个人可以耐受,4个输出通道和读取模式,以最大程度地减少跳过框架的数量(快速或Bright2)。我们还描述了一种协方差加权方案,该方案可以显着将贡献从1/F噪声降低,而与总和提取相比。我们评估了预放大器偏移,随机电报噪声和高深度电流RC像素所引入的噪声,发现一旦执行背景减法和像素掩蔽,这些噪声可在10 ppm以下进行纠正。我们在同伴论文中探索系统的错误来源。

JWST transmission and emission spectra will provide invaluable glimpses of transiting exoplanet atmospheres, including possible biosignatures. This promising science from JWST, however, will require exquisite precision and understanding of systematic errors that can impact the time series of planets crossing in front of and behind their host stars. Here, we provide estimates of the random noise sources affecting JWST NIRCam time-series data on the integration-to-integration level. We find that 1/f noise can limit the precision of grism time series for 2 groups (230 ppm to 1000 ppm depending on the extraction method and extraction parameters), but will average down like the square root of N frames/reads. The current NIRCam grism time series mode is especially affected by 1/f noise because its GRISMR dispersion direction is parallel to the detector fast-read direction, but could be alleviated in the GRISMC direction. Care should be taken to include as many frames as possible per visit to reduce this 1/f noise source: thus, we recommend the smallest detector subarray sizes one can tolerate, 4 output channels and readout modes that minimize the number of skipped frames (RAPID or BRIGHT2). We also describe a covariance weighting scheme that can significantly lower the contributions from 1/f noise as compared to sum extraction. We evaluate the noise introduced by pre-amplifier offsets, random telegraph noise, and high dark current RC pixels and find that these are correctable below 10 ppm once background subtraction and pixel masking are performed. We explore systematic error sources in a companion paper.

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