Fast interferometric data from the Very Large Array for Fast Radio Burst FRB 190520

Data products to support reproduction of the interferometric localization of Fast Radio Burst 190520. The principle data products are tar files of fast-sampled interferometric data from the Very Large Array (download separately to avoid dataverse file size limit). Each observation segment includes a few seconds of visibilities centered on a radio burst from FRB 190520. Data is in science data model (SDM) format, which consists of a directory with metadata in XML files and binary data in the ASDMBinary subdirectory. Binary data were recorded with an integration time of 10 ms and dual-circular polarizations. Each file is identified by a unique name of the observation, plus the observation start time in MJD. Each visibility data set is associated with one of the calibration files with the same MJD (telcal format; ending in \".GN\") that can be parsed to apply gain calibration. The Python package rtpipe (https://github.com/realfastvla/rfpipe) can perform all calibration and analysis of these data. This library is supported by sdmpy (https://github.com/demorest/sdmpy), a Python library to read SDM files. See also http://realfast.io for information on the project behind the data acquisition system and analysis software.

本数据集用于支持快速射电暴190520（Fast Radio Burst 190520）干涉定位结果的复现工作。其核心数据产品为甚大阵（Very Large Array, VLA）采集的快速采样干涉测量数据的tar归档文件，需单独下载以规避Dataverse平台的文件大小限制。每一段观测片段均包含以FRB 190520射电暴为中心的数秒时长的可见度数据。数据采用科学数据模型（Science Data Model, SDM）格式，该格式由存储XML元数据的目录与存放二进制数据的ASDMBinary子目录组成。二进制数据的积分时间为10毫秒，且包含双圆极化信号。每个文件通过观测的唯一名称与以修正儒略日（Modified Julian Date, MJD）标注的观测起始时间进行标识。每一组可见度数据集均关联一组同MJD的校准文件（telcal格式，后缀为".GN"），此类文件可被解析以完成增益校准。Python工具包rtpipe（https://github.com/realfastvla/rfpipe）可对上述数据完成全部校准与分析工作，该工具包依赖sdmpy（https://github.com/demorest/sdmpy）——一款用于读取SDM文件的Python库。如需了解数据采集系统与分析软件背后的项目详情，请访问http://realfast.io。