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arXiv 2303.02525astro-ph.HEastro-ph.IM
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利用 Vera C. Rubin 天文台快速探测快速光学暴

Prompt Detection of Fast Optical Bursts with the Vera C. Rubin Observatory

Guillem Megias Homar, Joshua E. Meyers, Steven M. Kahn

AI总结:

本文提出通过识别视宁度造成的异常空间图像来探测毫秒级 FOB,并基于 Rubin 光子追踪模拟和神经网络分类,给出识别约束及 LSST 十年内 FRB 光学对应体的预期探测数。

摘要:

瞬变光学天空在极短时间尺度上仍基本未被探索。尽管已有一些实验搜索从分钟到年级时间尺度的光学瞬变源,但没有任何实验具备分辨毫秒级快速光学暴(Fast Optical Bursts,FOB)的能力。这种极快瞬变源可能是快速射电暴(Fast Radio Bursts,FRB)的光学对应体、γ射线暴(γ-Ray Bursts,GRB)的瞬时辐射,或其他此前未知的现象。本文研究了一种用于偶然探测 FOB 的新方法,其核心是搜索异常的空间图像。具体而言,由于 FOB 持续时间很短,在有限时长的标准光学曝光中,受视宁度畸变的 FOB 图像应表现出与稳定光源图像明显不同的特征。我们将这一思想应用于 Vera C. Rubin 天文台的模拟观测;这些模拟通过追踪单个光子穿过湍流大气,并继续向下经过 Rubin 望远镜的光学系统和相机而生成。我们将这些模拟图像与在 15 s 积分时间(Rubin 的标称曝光时间)下得到的稳定源恒星模拟进行比较。本文报告了用于区分 FOB 与稳定源的神经网络分类器的分类准确率结果。基于该分类器,我们给出了在持续时间—强度参数空间中对 Rubin 观测中的 FOB 进行明确识别的约束条件。最后,我们估计了在为期 10 年的 Rubin 空间与时间遗留巡天(Legacy Survey of Space and Time,LSST)期间,预计可探测到的 FRB 的 FOB 对应体总数。

英文摘要:

The transient optical sky has remained largely unexplored on very short timescales. While there have been some experiments searching for optical transients from minutes to years, none have had the capability to distinguish millisecond Fast Optical Bursts (FOB). Such very fast transients could be the optical counterparts of Fast Radio Bursts (FRB), the prompt emission from $γ$-Ray Bursts (GRB), or other previously unknown phenomena. Here, we investigate a novel approach to the serendipitous detection of FOBs, which relies on searching for anomalous spatial images. In particular, due to their short duration, the seeing distorted images of FOBs should look characteristically different than those of steady sources in a standard optical exposure of finite duration. We apply this idea to simulated observations with the Vera C. Rubin Observatory, produced by tracing individual photons through a turbulent atmosphere, and down through the optics and camera of the Rubin telescope. We compare these simulated images to steady-source star simulations in 15 s integrations, the nominal Rubin exposure time. We report the classification accuracy results of a Neural Network classifier for distinguishing FOBs from steady sources. From this classifier, we derive constraints in duration-intensity parameter space for unambiguously identifying FOBs in Rubin observations. We conclude with estimates of the total number of detections of FOB counterparts to FRBs expected during the 10-year Rubin Legacy Survey of Space and Time (LSST).

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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