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基于CSST的暂现源探测方法

Transient Detection Method Based on CSST

  • 摘要: 中国巡天空间望远镜(China Space Survey Telescope, CSST)是中国载人航天工程规划建设的以大规模天文巡天为主任务的2m口径空间光学望远镜, 兼具高空间分辨率与大视场特性, 性能优异. 暂现源是CSST的重要科学目标之一. CSST作为空间望远镜, 与地面望远镜的图像噪声组成有着明显不同. 因此, 不能直接套用先前地基巡天项目的暂现源探测方案, 需要针对性开发专属的探测方法. CSST的暂现源探测方法以CSST仿真数据为基础进行开发、验证, 旨在尽可能准确地识别CSST主巡天数据中的暂现源. 方法以图像相减法为基础, 首先获得观测图像所对应残差图像, 并利用滤波方法给出残差图像泊松噪声分布; 然后使用渐变阈值间接统一背景噪声水平, 对残差图像进行目标源测光得到候选源列表; 最后, 通过判断候选源与当地泊松噪声的偏差对真实暂现源进行筛选, 结合原始图像信息与观测图像测光分类信息后, 进一步对候选源列表的假源进行剔除, 最终输出暂现源星表. 方法在共计20000个暂现源的多轮仿真测试中, 能够以平均95.9%的准确率对观测图像中的暂现源进行筛选. 相较于先前工作, 还更加全面且定量地给出了测试所得的不同亮度暂现源所对应的探测率. 测试结论验证了CSST暂现源探测方法的可行性、泛化能力与稳定性. 该方法也为空间望远镜暂现源探测任务提供了理论与编程基础.

     

    Abstract: China Space Survey Telescope (CSST) is a 2-meter aperture optical space telescope planned by the China Manned Space Program, with the primary focus on large-scale surveys, which combines high spatial resolution and a large field of view. Transients are one of the important scientific objectives of CSST. As a space telescope, the image noise composition of CSST is significantly different from that of ground-based telescopes. Therefore, it is unsuitable to directly apply the transient detection scheme of previous ground-based survey project, and it is necessary to develop an independent detection method for CSST. The CSST transient detection method is developed and validated based on the CSST simulation data, aiming to identify transients in CSST main survey data as accurately as possible. The method is based on Difference Image Analysis (DIA) method, which firstly obtains the residual images corresponding to the observed image, and then uses filtering method to obtain the local Poisson noise distribution of the residual image. The method then uses a changing threshold to indirectly unify the image noise level, and performs photometry and source extraction on the residual image to obtain a list of candidate sources. Next, the real sources are filtered by judging the deviation of the candidate sources from local Poisson noise. After combining the photometric classification information of the observed image and the information of original image, the fake sources in the candidate source list are further eliminated. The final output is a transient list. The method is able to filter transients in the observed images with an average accuracy of 95.9% in a multi-round simulation test with a total of 20000 transients. Compared with the previous work, the test also quantifies the detection rates of transients with different brightness more comprehensively. The conclusions of the test validate the feasibility, generalisation and stability of the CSST transient detection method. The method also provides a theoretical and programming basis for transient detection mission of space telescopes.

     

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