SPARKESX: Single-dish PARKES data sets for finding the uneXpected - Part 3

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)我们提出了用于发现未知意外信号的单口径帕克斯（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仿真的高时间分辨率观测数据。SPARKESX包含来自帕克斯"穆里扬"（Murriyang）射电望远镜的三次模拟巡天项目。每次巡天都将生成大量经过仿真与注入的预期信号（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）以及完全未知的未知信号。我们基于标准脉冲星搜索软件PRESTO搭建了典型处理流水线，并给出其在识别注入信号时的表现，以此作为基准性能参照。本数据集旨在助力新型搜索算法的研发，涵盖图像处理、机器学习以及深度学习相关算法。数据集包含原始数据、真值标签以及基准性能结果。本数据集共分为4个部分，相关分块详情请参见关联链接： 1. 第一部分：真值标签、注入图像与多波束数据集 2. 第二部分：PAF数据集 3. 第三部分：PAF数据集 4. 第四部分：PAF数据集 相关文献：《SPARKESX：用于发现未知意外信号的单口径帕克斯数据集——一项数据挑战赛》（Yong等人，2022年，已投稿）

搜集汇总

背景与挑战

背景概述

SPARKESX Part 3是SPARKESX项目的一部分，旨在为开发新搜索算法（如图像处理、机器学习和深度学习）提供高时间分辨率观测数据。该数据集包含来自Parkes 'Murriyang' 射电望远镜的PAF数据集，涉及模拟和注入的已知和未知信号，如脉冲星和快速射电暴，并提供了原始数据、地面真实标签和基线，以支持算法测试和优化。