您选择的条件: Zhijun Xu
  • OmniUV: A Multi-Purpose Simulation Toolkit for VLBI Observation

    分类: 天文学 >> 天文学 提交时间: 2023-02-19

    摘要: We present OmniUV, a multi-purpose simulation toolkit for space and ground VLBI observations. It supports various kinds of VLBI stations, including Earth (ground) fixed, Earth orbit, Lunar fixed, Lunar orbit, Moon-Earth and Earth-Sun Lagrange 1 and 2 points, etc. The main functionalities of this toolkit are: (1) Trajectory calculation; (2) Baseline uv calculation, by taking the vailability of each station into account; (3) Visibility simulation for the given uv distribution, source structure and system noise; (4) Image and beam reconstruction. Two scenarios, namely space VLBI network and wide field array, are presented as demonstrations of the toolkit applications in completely different scales. OmniUV is the acronym of "Omnipotent UV". We hope it could work as a general framework, in which various kinds of stations could be easily incorporated and the functionalities could be further extended. The toolkit has been made publicly available.

  • VOLKS2: a transient search and localization pipeline for VLBI observations

    分类: 天文学 >> 天文学 提交时间: 2023-02-19

    摘要: We present VOLKS2, the second release of "VLBI Observation for transient Localization Keen Searcher". The pipeline aims at transient search in regular VLBI observations as well as detection of single pulses from known sources in dedicated VLBI observations. The underlying method takes the idea of geodetic VLBI data processing, including fringe fitting to maximize the signal power and geodetic VLBI solving for localization. By filtering the candidate signals with multiple windows within a baseline and by cross matching with multiple baselines, RFIs are eliminated effectively. Unlike the station auto spectrum based method, RFI flagging is not required in the VOLKS2 pipeline. EVN observation (EL060) is carried out, so as to verify the pipeline's detection efficiency and localization accuracy in the whole FoV. The pipeline is parallelized with MPI and further accelerated with GPU, so as to exploit the hardware resources of modern GPU clusters. We can prove that, with proper optimization, VOLKS2 could achieve comparable performance as auto spectrum based pipelines. All the code and documents are publicly available, in the hope that our pipeline is useful for radio transient studies.

  • Status and progress of China SKA Regional Centre prototype

    分类: 天文学 >> 天文学 提交时间: 2023-02-19

    摘要: The Square Kilometre Array (SKA) project consists of delivering two largest radio telescope arrays being built by the SKA Observatory (SKAO), which is an intergovernmental organization bringing together nations from around the world with China being one of the major member countries. The computing resources needed to process, distribute, curate and use the vast amount of data that will be generated by the SKA telescopes are too large for the SKAO to manage on its own. To address this challenge, the SKAO is working with the international community to create a shared, distributed data, computing and networking capability called the SKA Regional Centre Alliance. In this model, the SKAO will be supported by a global network of SKA Regional Centres (SRCs) distributed around the world in its member countries to build an end-to-end science data system that will provide astronomers with high-quality science products. SRCs undertake deep processing, scientific analysis, and long-term storage of the SKA data, as well as user support. China has been actively participating in and promoting the construction of SRCs. This paper introduces the international cooperation and ongoing prototyping of the global SRC network, the construction plan of the China SRC and describes in detail the China SRC prototype. The paper also presents examples of scientific applications of SKA precursor and pathfinder telescopes completed using resources from the China SRC prototype. Finally, the future prospects of the China SRC are presented.

  • Artificial intelligence for celestial object census: the latest technology meets the oldest science

    分类: 天文学 >> 天文学 提交时间: 2023-02-19

    摘要: Large surveys using modern telescopes are producing images that are increasing exponentially in size and quality. Identifying objects in the generated images by visual recognition is time-consuming and labor-intensive, while classifying the extracted radio sources is even more challenging. To address these challenges, we develop a deep learning-based radio source detector, named \textsc{HeTu}, which is capable of rapidly identifying and classifying radio sources in an automated manner for both compact and extended radio sources. \textsc{HeTu} is based on a combination of a residual network (ResNet) and feature pyramid network (FPN). We classify radio sources into four classes based on their morphology. The training images are manually labeled and data augmentation methods are applied to solve the data imbalance between the different classes. \textsc{HeTu} automatically locates the radio sources in the images and assigns them to one of the four classes. The experiment on the testing dataset shows an average operation time of 5.4 millisecond per image and a precision of 99.4\% for compact point-like sources and 98.1\% for double-lobe sources. We applied \textsc{HeTu} to the images obtained from the GaLactic and the Galactic Extragalactic All-Object Murchison Wide-field Array (GLEAM) survey project. More than 96.9\% of the \textsc{HeTu}-detected compact sources are matched compared to the source finding software used in the GLEAM. We also detected and classified 2,298 extended sources (including Fanaroff-Riley type I and II sources, and core-jet sources) above $5\sigma$. The cross-matching rates of extended sources are higher than 97\%, showing excellent performance of \textsc{HeTu} in identifying extended radio sources. \textsc{HeTu} provides an efficient tool for radio source finding and classification and can be applied to other scientific fields.

  • Status and progress of China SKA Regional Centre prototype

    分类: 天文学 >> 天文学 提交时间: 2023-02-19

    摘要: The Square Kilometre Array (SKA) project consists of delivering two largest radio telescope arrays being built by the SKA Observatory (SKAO), which is an intergovernmental organization bringing together nations from around the world with China being one of the major member countries. The computing resources needed to process, distribute, curate and use the vast amount of data that will be generated by the SKA telescopes are too large for the SKAO to manage on its own. To address this challenge, the SKAO is working with the international community to create a shared, distributed data, computing and networking capability called the SKA Regional Centre Alliance. In this model, the SKAO will be supported by a global network of SKA Regional Centres (SRCs) distributed around the world in its member countries to build an end-to-end science data system that will provide astronomers with high-quality science products. SRCs undertake deep processing, scientific analysis, and long-term storage of the SKA data, as well as user support. China has been actively participating in and promoting the construction of SRCs. This paper introduces the international cooperation and ongoing prototyping of the global SRC network, the construction plan of the China SRC and describes in detail the China SRC prototype. The paper also presents examples of scientific applications of SKA precursor and pathfinder telescopes completed using resources from the China SRC prototype. Finally, the future prospects of the China SRC are presented.