The Bright Transient Survey (BTS) aims to obtain a classification spectrum for all bright (m _peak ≤ 18.5 mag) extragalactic transients found in the Zwicky Transient Facility (ZTF) public survey. BTS critically relies on visual inspection (“scanning”) to select targets for spectroscopic follow-up, which, while effective, has required a significant time investment over the past ∼5 yr of ZTF operations. We present BTSbot, a multimodal convolutional neural network, which provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. BTSbot is able to eliminate the need for daily human scanning by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. BTSbot recovers all bright transients in our test split and performs on par with scanners in terms of identification speed (on average, ∼1 hr quicker than scanners). We also find that BTSbot is not significantly impacted by any data shift by comparing performance across a concealed test split and a sample of very recent BTS candidates. BTSbot has been integrated into Fritz and Kowalski, ZTF’s first-party marshal and alert broker, and now sends automatic spectroscopic follow-up requests for the new transients it identifies. Between 2023 December and 2024 May, BTSbot selected 609 sources in real time, 96% of which were real extragalactic transients. With BTSbot and other automation tools, the BTS workflow has produced the first fully automatic end-to-end discovery and classification of a transient, representing a significant reduction in the human time needed to scan.

中文翻译：

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兹威基瞬态设施明亮瞬态调查。三． BTSbot：通过深度学习自动识别和跟踪明亮瞬变


明亮瞬变巡天 (BTS) 旨在获得兹威基瞬变设施 (ZTF) 公共巡天中发现的所有明亮（m_峰值≤ 18.5 星等）河外瞬变的分类谱。 BTS 严重依赖目视检查（“扫描”）来选择光谱跟踪的目标，这虽然有效，但在过去约 5 年的 ZTF 运营中需要投入大量时间。我们推出了 BTSbot，一种多模态卷积神经网络，它使用图像数据和 25 个提取的特征为单个 ZTF 检测提供明亮的瞬态分数。 BTSbot 能够通过自动识别和请求对新的明亮瞬态候选者进行光谱后续观察来消除日常人工扫描的需要。 BTSbot 在我们的测试中恢复了所有明亮的瞬态，并且在识别速度方面与扫描仪的性能相当（平均比扫描仪快约 1 小时）。通过比较隐藏测试分组和最近 BTS 候选样本的性能，我们还发现 BTSbot 并未受到任何数据变化的显着影响。 BTSbot 已集成到 ZTF 的第一方编组和警报代理 Fritz 和 Kowalski 中，现在针对其识别的新瞬变发送自动光谱后续请求。 2023年12月至2024年5月期间，BTSbot实时选择了609个源，其中96%是真实的河外瞬变。借助 BTSbot 和其他自动化工具，BTS 工作流程首次实现了瞬态的全自动端到端发现和分类，这意味着扫描所需的人工时间显着减少。