论文标题
GWSKYNET：公共重力波候选人的实时分类器
GWSkyNet: a real-time classifier for public gravitational-wave candidates
论文作者
论文摘要
重力波候选者准确的天空定位的快速释放对于多通信器观察至关重要。在第三次观测高级Ligo和高级处女座运行期间，自动重力波警报在检测后的几分钟内公开发布。随后的检查和分析导致最终撤回一部分候选人。更新可能会延迟长达几天，有时会在详尽的多理智随访活动期间或之后发布。我们介绍了Gwskynet，这是一个实时框架，旨在仅使用Ligo-Virgo公开公共警报中的公开信息来区分天体物理事件和乐器人工制品。该框架由涉及天空图和元数据的非序列卷积神经网络组成。 GWSKYNET在测试数据集上实现了93.5％的预测准确性。
The rapid release of accurate sky localization for gravitational-wave candidates is crucial for multi-messenger observations. During the third observing run of Advanced LIGO and Advanced Virgo, automated gravitational-wave alerts were publicly released within minutes of detection. Subsequent inspection and analysis resulted in the eventual retraction of a fraction of the candidates. Updates could be delayed by up to several days, sometimes issued during or after exhaustive multi-messenger followup campaigns. We introduce GWSkyNet, a real-time framework to distinguish between astrophysical events and instrumental artefacts using only publicly available information from the LIGO-Virgo open public alerts. This framework consists of a non-sequential convolutional neural network involving sky maps and metadata. GWSkyNet achieves a prediction accuracy of 93.5% on a testing data set.
