Dissemin is shutting down on January 1st, 2025

Published in

Oxford University Press, Monthly Notices of the Royal Astronomical Society, 4(516), p. 5832-5848, 2022

DOI: 10.1093/mnras/stac2558

Links

Tools

Export citation

Search in Google Scholar

SPARKESX: Single-dish PARKES data sets for finding the uneXpected – a data challenge

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

ABSTRACT New classes of astronomical objects are often discovered serendipitously. The enormous data volumes produced by recent high-time resolution, radio-telescope surveys imply that efficient algorithms are required for a discovery. Such algorithms are usually tuned to detect specific, known sources. Existing data sets therefore likely contain unknown astronomical sources, which will remain undetected unless algorithms are developed that can detect a more diverse range of signals. 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 and fast radio bursts), poorly characterized signals (plausible flare star signatures), and ‘unknown unknowns’ are generated for each survey. The goal of this challenge is to aid in the development of new algorithms that can detect a wide range of source types. We show how successful a typical pipeline based on the standard pulsar search software, presto, is at finding the injected signals. The data set is publicly available at https://doi.org/10.25919/fd4f-0g20 (Yong et al. 2022).