Pulsar searches and timing with the square kilometre array

¹ Jodrell Bank Centre for Astrophysics, University of Manchester, UK e-mail: Roy.Smits@manchester.ac.uk
² Department of Physics, 210 Hodges Hall, West Virginia University, Morgantown, WV 26506, USA
³ National Radio Astronomy Observatory, Green Bank, USA
⁴ Astronomy Department, Cornell University, Ithaca, NY, USA

Received: 13 June 2008
Accepted: 31 October 2008

Abstract

The square kilometre array (SKA) is a planned multi purpose radio telescope with a collecting area approaching 1 million square metres. One of the key science objectives of the SKA is to provide exquisite strong-field tests of gravitational physics by finding and timing pulsars in extreme binary systems such as a pulsar-black hole binary. To find out how three preliminary SKA configurations will affect a pulsar survey, we have simulated SKA pulsar surveys for each configuration. We estimate that the total number of pulsars the SKA will detect, is around 14 000 normal pulsars and 6000 millisecond pulsars, using only the 1-km core and 30-mn integration time. We describe a simple strategy for follow-up timing observations and find that, depending on the configuration, it would take 1–6 days to obtain a single timing point for 14 000 pulsars. Obtaining one timing point for the high-precision timing projects of the SKA, will take less than 14 h, 2 days, or 3 days, depending on the configuration. The presence of aperture arrays will be of great benefit here. We also study the computational requirements for beam forming and data analysis for a pulsar survey. Beam forming of the full field of view of the single-pixel feed 15-m dishes using the 1-km core of the SKA requires about 2.2 10¹⁵ operations per second. The corresponding data rate from such a pulsar survey is about 4.7 10¹¹ bytes per second. The required computational power for a deep real time analysis is estimated to be 1.2 10¹⁶ operations per second. For an aperture array or dishes equipped with phased array feeds, the survey can be performed faster, but the computational requirements and data rates will go up.