发表机构
Western University; Western University, Institute for Earth and Space Exploration（韦仕敦大学; 韦仕敦大学地球与太空探索研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出分组差分方法处理JWST NIRCam斜坡数据，缩短移动源拖尾，提高信噪比与探测灵敏度，模拟显示灵敏度增益约1.1至1.4星等。
AI 中文摘要
JWST档案中包含数千张分布在天球上的NIRCam曝光图像。许多这类视场中存在小型太阳系天体（SSSBs），但它们常常出现拖尾现象，因此更难被探测到。标准处理流程通过对探测器$N$个累积的“斜坡上升”组序列拟合斜率来生成单张图像。因此，每张JWST图像都包含一系列累积读数的时间序列。我们证明，将斜坡转换为一系列组差分图像可以减少移动源在每张图像中的拖尾长度，从而从$N$组积分中产生$(N-1)$组的光度校准时间序列。这使得仅利用单次JWST曝光即可进行更高频率的基于轨迹的搜索。对沿移动源轨迹的组差分图像进行广义最小二乘拟合，与斜坡拟合相比，能以更高的信噪比恢复源通量，且改善程度随拖尾减少而增加。我们在档案JWST NIRCam图像中探测到的13个移动天体上验证了该流程。为估计灵敏度提升，我们在JWST图像上进行了注入/恢复模拟。通过组差分恢复的拖尾移动天体显示出更高的信噪比，与标准校准相比，提高了对移动源的完备性。对于黄道面上档案JWST/NIRCam曝光的典型积分长度$N=4$或$6$，基于模拟结果，组差分带来的灵敏度增益约为$1.1$至$1.4$星等。该方法显著提高了档案JWST巡天对拖尾SSSBs的灵敏度。
英文摘要
The JWST archive contains thousands of NIRCam exposures distributed across the sky. Small solar system bodies (SSSBs) are present in many of these fields, but are often trailed and more difficult to detect. The standard pipeline produces a single image by fitting a slope to a sequence of $N$ cumulative ``up-the-ramp" groups of the detector. Thus, each JWST image comprises a time series of cumulative reads. We demonstrate that transforming the ramp into a series of group difference images reduces the per-image trail length of moving sources, producing an $(N-1)$-group photometrically calibrated time series from an $N$-group integration. This enables higher-cadence trajectory-based searches using as few as a single JWST exposure. A generalized least-squares fit of the group difference images along the trajectory of a moving source recovers the source flux at higher SNR when compared to the ramp fit, with the improvement scaling with the reduction in trailing. We validate our procedure on 13 moving objects detected in archival JWST NIRCam images. To estimate our sensitivity increase, we perform an injection/recovery simulation on the JWST imagery. Trailed moving objects recovered via group differencing show higher SNRs, improving completeness to moving sources compared to standard calibrations. For typical integration lengths of $N=4$ or $6$ for archival JWST/NIRCam exposures in the ecliptic, group differencing yields sensitivity gains between $\sim 1.1$--$1.4$ mag, based on simulation results. This method significantly increases the sensitivity of archival JWST surveys to trailed SSSBs.
Comments21 pages, 12 figures, 4 tables. Accepted for publication in AJ. Code available at https://github.com/Corrado777/JWST-Ramp-Slicer
