SPARKESX: Single-dish PARKES data sets for finding the uneXpected - Part 4

We present the Single-dish PARKES data sets for finding the uneXpected (SPARKESX), a compilation of real and simulated high-time resolution observations. SPARKESX comprises three mock surveys from the Parkes ''Murriyang'' radio telescope. A broad selection of simulated and injected expected signals (such as pulsars, fast radio bursts), poorly known signals (such as the features expected from flare stars) and unknown unknowns are generated for each survey. We provide a baseline by presenting how successful a typical pipeline based on the standard pulsar search software, PRESTO, is at finding the injected signals. The dataset is designed to aid in the development of new search algorithms, including image processing, machine learning, and deep learning. The raw data, ground truth labels, and baseline are provided. The collection is split into 4 parts. See collections in related links. Part 1 - Ground truth labels, injected images, multibeam dataset Part 2 - PAF dataset Part 3 - PAF dataset Part 4 - PAF dataset Publication: SPARKESX: Single-dish PARKES data sets for finding the uneXpected - A data challenge (Yong et a. 2022, submitted)我们提出了用于搜寻意外现象的单口径帕克斯（Parkes）数据集（Single-dish PARKES data sets for finding the uneXpected，缩写SPARKESX），该数据集整合了真实与模拟的高时间分辨率观测结果。SPARKESX包含来自帕克斯“穆里扬”（Murriyang）射电望远镜的三次模拟巡天观测。针对每一次巡天，我们生成了多类模拟与注入信号：包括预期信号（例如脉冲星、快速射电暴）、认知有限的信号（例如耀星预期产生的特征）以及未知的未知信号。我们通过展示基于标准脉冲星搜寻软件PRESTO构建的典型处理流程在探测注入信号方面的表现，提供了基准性能参照。本数据集旨在助力新型搜寻算法的开发，涵盖图像处理、机器学习与深度学习方向。数据集包含原始数据、真实标注标签以及基准性能数据。本数据集分为四个部分，相关链接中可查看各部分详情：第一部分：真实标注标签、注入信号图像与多波束数据集；第二部分：PAF数据集；第三部分：PAF数据集；第四部分：PAF数据集。相关文献：《SPARKESX：用于搜寻意外现象的单口径帕克斯数据集——一项数据挑战赛》（Yong等，2022，已投稿）