4.6 Article

Pulsar searches and timing with the square kilometre array

Journal

ASTRONOMY & ASTROPHYSICS
Volume 493, Issue 3, Pages 1161-1170

Publisher

EDP SCIENCES S A
DOI: 10.1051/0004-6361:200810383

Keywords

stars: neutron; stars: pulsars: general; telescopes

Funding

  1. European Community
  2. Square Kilometre Array Design Studies (SKADS) [011938]
  3. West Virginia EPSCoR
  4. NSF [AST0507747]

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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 x 10(15) operations per second. The corresponding data rate from such a pulsar survey is about 4.7 x 10(11) bytes per second. The required computational power for a deep real time analysis is estimated to be 1.2 x 10(16) 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.

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