用于警报流实时分类的多尺度stamp
Multi-scale stamps for real-time classification of alert streams
AI总结：
针对Rubin警报中卫星闪光导致误分类的问题，本文提出等像素预算的多尺度stamp方案，在不增加带宽负担的情况下达到接近15倍大高分辨率stamp的分类效果。
AI中文摘要：
近年来，图像裁剪图（也称为“stamp”）的自动分类器已被证明是快速超新星发现的关键。Vera C. Rubin天文台每晚将分发约一千万条警报及其各自的stamp，从而每年能够发现约一百万颗超新星。对这些分类器而言，一个日益严重的混淆来源是卫星闪光，即由旋转卫星或碎片产生的一系列点状源。目前规划的Rubin stamp尺寸将小于这些点状源之间的典型间距。因此，更大视场的stamp可能实现对这些源的自动识别。然而，更大stamp的分发会受到网络带宽限制。我们使用Zwicky Transient Facility的数据，评估了采用不同角尺寸和分辨率的图像stamp对事件（AGN、小行星、伪源、卫星、SNe和变星）进行快速分类的影响。我们比较了四种情形：三种具有相同像素数（高分辨率小视场、低分辨率大视场，以及一种多尺度方案），另一种是具有更大视场和更高分辨率的完整stamp。与小视场stamp相比，我们的多尺度策略减少了将卫星误分类为小行星或超新星的情况，其性能与数据量大15倍的高分辨率stamp相当。我们鼓励Rubin及其科学合作组织考虑实施多尺度stamp的益处，将其作为警报规范的可能更新。
英文摘要：
In recent years, automatic classifiers of image cutouts (also called "stamps") have shown to be key for fast supernova discovery. The Vera C. Rubin Observatory will distribute about ten million alerts with their respective stamps each night, enabling the discovery of approximately one million supernovae each year. A growing source of confusion for these classifiers is the presence of satellite glints, sequences of point-like sources produced by rotating satellites or debris. The currently planned Rubin stamps will have a size smaller than the typical separation between these point sources. Thus, a larger field of view stamp could enable the automatic identification of these sources. However, the distribution of larger stamps would be limited by network bandwidth restrictions. We evaluate the impact of using image stamps of different angular sizes and resolutions for the fast classification of events (AGNs, asteroids, bogus, satellites, SNe, and variable stars), using data from the Zwicky Transient Facility. We compare four scenarios: three with the same number of pixels (small field of view with high resolution, large field of view with low resolution, and a multi-scale proposal) and a scenario with the full stamp that has a larger field of view and higher resolution. Compared to small field of view stamps, our multi-scale strategy reduces misclassifications of satellites as asteroids or supernovae, performing on par with high-resolution stamps that are 15 times heavier. We encourage Rubin and its Science Collaborations to consider the benefits of implementing multi-scale stamps as a possible update to the alert specification.
