Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

earth and planetary sciences

Open Universe survey of Swift -XRT GRB fields: Flux-limited sample of HBL blazars

Astronomy and Astrophysics, Volume 642, Article A141, Year 2020

Aims. The sample of serendipitous sources detected in all Swift-XRT images pointing at gamma ray bursts (GRBs) constitutes the largest existing medium-deep survey of the X-ray sky. To build such dataset we analysed all Swift X-ray images centred on GRBs and observed over a period of 15 years using automatic tools that do not require any expertise in X-ray astronomy. Besides presenting a new large X-ray survey and a complete sample of blazars, this work aims to be a step in the direction of achieving the ultimate goal of the Open Universe Initiative, which is to enable non-expert people to benefit fully from space science data, possibly extending the potential for scientific discovery, which is currently confined within a small number of highly specialised teams, to a much larger population. Methods. We used the Swift_deepsky Docker container encapsulated pipeline to build the largest existing flux-limited and unbiased sample of serendipitous X-ray sources. Swift_deepsky runs on any laptop or desktop computer with a modern operating system. The tool automatically downloads the data and the calibration files from the archives, runs the official Swift analysis software, and produces a number of results including images, the list of detected sources, X-ray fluxes, spectral energy distribution data, and spectral slope estimations. Results. We used our source list to build the LogN-LogS of extra-galactic sources, which perfectly matches that estimated by other satellites. Combining our survey with multi-frequency data, we selected a complete radio-flux-density-limited sample of high energy peaked blazars (HBL). The LogN-LogS built with this data set confirms that previous samples are incomplete below ∼20 mJy.

Statistics
Citations: 25
Authors: 25
Affiliations: 17
Identifiers
Study Design
Cross Sectional Study
Study Approach
Quantitative