Artificial neural networks for selection of pulsar candidates from radio continuum surveys
Artificial neural networks for selection of pulsar candidates from radio continuum surveys
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DOI：
10.1093/mnras/staa742
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发表时间：
2018-11
影响因子：
4.8
通讯作者：
Naoyuki Yonemaru;Keitaro Takahashi;H. Kumamoto;S. Dai;S. Yoshiura;S. Ideguchi
中科院分区：
文献类型：
--
作者：
Naoyuki Yonemaru;Keitaro Takahashi;H. Kumamoto;S. Dai;S. Yoshiura;S. Ideguchi
使用时域观测来搜索脉冲星在计算上是非常昂贵的，而下一代望远镜（如平方公里阵列）的数据量将是巨大的。我们使用人工神经网络（ANNs），一种机器学习方法，从射电连续体调查中有效地选择脉冲星候选者；这比使用时域观测便宜得多。以射电通量、天空位置和致密度等观测量作为输入，我们的人工神经网络输出“分数”，表明一个物体是脉冲星的可能性程度。我们基于塔塔基础研究所（TIFR）巨型米波射电望远镜（GMRT）巡天（TGSS）和国家射电天文台（NRAO）甚大阵列（VLA）巡天（NVSS）的现有巡天数据演示了人工神经网络，并测试了它们的性能。精确度，即正确分类为脉冲星的脉冲星数量与任何分类为脉冲星的物体数量之比，约为96 {{\ \ \rm}}$。最后，我们将训练好的神经网络应用于未识别的射电源，我们的基准神经网络具有五个输入（银河系的经纬度、TGSS和NVSS通量以及紧致度），从456866个未识别的射电源中生成2436个脉冲星候选者。我们需要通过时域观测来确认这些候选者是否真的是脉冲星。两极分化等更多的信息将进一步缩小候选人的范围。
It is very computationally expensive to search for pulsars using time-domain observations, and the volume of data will be enormous with next-generation telescopes such as the Square Kilometre Array. We use artificial neural networks (ANNs), a machine learning method, for the efficient selection of pulsar candidates from radio continuum surveys; this is much cheaper than using time-domain observations. With observed quantities such as radio fluxes, sky position and compactness as inputs, our ANNs output the ‘score’ that indicates the degree of likeliness that an object is a pulsar. We demonstrate ANNs based on existing survey data by the Tata Institute for Fundamental Research (TIFR) Giant Metrewave Radio Telescope (GMRT) Sky Survey (TGSS) and the National Radio Astronomy Observatory (NRAO) Very Large Array (VLA) Sky Survey (NVSS) and we test their performance. The precision, which is the ratio of the number of pulsars classified correctly as pulsars to the number of any objects classified as pulsars, is about $96 {{\ \rm per\ cent}}$. Finally, we apply the trained ANNs to unidentified radio sources and our fiducial ANN with five inputs (the galactic longitude and latitude, the TGSS and NVSS fluxes and compactness) generates 2436 pulsar candidates from 456 866 unidentified radio sources. We need to confirm whether these candidates are truly pulsars by using time-domain observations. More information, such as polarization, will narrow the number of candidates down further.