five

Parkes observations for project P858 semester 2015APRS_BPSR_37

收藏
Research Data Australia2024-12-14 收录
下载链接:
https://researchdata.edu.au/parkes-observations-project-semester-2015aprsbpsr37/638640
下载链接
链接失效反馈
官方服务:
资源简介:
SUPERB is a large-scale survey for pulsars and extragalactic radio bursts. It will uses optimised GPU codes to search for pulsars and fast radio bursts (FRBs), making discoveries in real time. Handling our data as it comes in is essential for the SKA Phase I era so this work applies directly to the high-data rates of next generation telescopes. The pulsars discovered will enable studies of the interstellar medium, allow us to more accurately constrain the MSP luminosity function (which informs estimates of the SKA yield of MSPs), tests of theories of gravity and several will contribute to the precision timing projects of the PPTA. The FRBs discovered will have much more associated information than all previous detections. Firstly the discovery lag will be ~1 second, rather than months/years. The Parkes observations will be shadowed by the Molonglo telescope to allow, for the first time, localisation of FRBs, and a host of optical and high-energy telescopes will then be triggered as appropriate. This is key for identifying FRB host galaxies, so as to solve the mystery of their progenitors. The survey will discover ~20 MSPs, ~100 slower pulsars and ~10 FRBs.

SUPERB是一项针对脉冲星与河外射电暴的大规模巡天项目。该项目将采用优化后的图形处理器(Graphics Processing Unit, GPU)代码开展脉冲星与快速射电暴(fast radio bursts, FRB)的搜寻工作,实现实时发现。在平方公里阵列(Square Kilometre Array, SKA)第一阶段的运行范式下,实时处理接收数据至关重要,因此本项目的工作可直接适配下一代望远镜的高数据速率场景。所发现的脉冲星将可用于星际介质研究,帮助我们更精准地限定毫秒脉冲星(millisecond pulsar, MSP)的光度函数(该函数可为平方公里阵列的毫秒脉冲星产出率估算提供依据),并用于引力理论检验;其中部分脉冲星还将助力帕克斯脉冲星计时阵列(Parkes Pulsar Timing Array, PPTA)的高精度计时项目。本次巡天发现的快速射电暴将拥有远超此前所有探测结果的关联信息:首先,其发现时延仅约1秒,而非数月乃至数年。帕克斯(Parkes)望远镜的观测将配合莫朗格洛(Molonglo)望远镜开展同步掩蔽观测,首次实现快速射电暴的定位;随后将根据需求触发一系列光学与高能望远镜开展后续观测。这对于确定快速射电暴的宿主星系至关重要,进而破解其起源之谜。该巡天项目预计将发现约20颗毫秒脉冲星、约100颗慢速脉冲星以及约10个快速射电暴。
提供机构:
Commonwealth Scientific and Industrial Research Organisation
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作