2009
DOI: 10.1103/physrevd.79.022001
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Einstein@Home search for periodic gravitational waves in LIGO S4 data

Abstract: A search for periodic gravitational waves, from sources such as isolated rapidly spinning neutron stars, was carried out using 510 h of data from the fourth LIGO science run (S4). The search was for quasimonochromatic waves in the frequency range from 50 to 1500 Hz, with a linear frequency drift f˙ (measured at the solar system barycenter) in the range -f/τ Show more

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Cited by 113 publications
(116 citation statements)
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“…The LSC uses both fully coherent [1][2][3][4][5] and semi-coherent [6][7][8][9] methods to search for periodic gravitational waves. Semi-coherent methods are computationally cheaper than coherent methods, but coherent methods can achieve greater sensitivity if the cost is feasible.…”
Section: Search Methodsmentioning
confidence: 99%
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“…The LSC uses both fully coherent [1][2][3][4][5] and semi-coherent [6][7][8][9] methods to search for periodic gravitational waves. Semi-coherent methods are computationally cheaper than coherent methods, but coherent methods can achieve greater sensitivity if the cost is feasible.…”
Section: Search Methodsmentioning
confidence: 99%
“…where μ is the mismatch and we have performed the integral in equation (24) of [34] using the ranges (9) and discarding the lower bound on frequency, which is only a few per cent correction. We determine the highest frequency derivative needed by finding k such that γ kk 2 k > μ, where k is the range of the kth frequency derivative and we take μ to be 20% (typical for periodic signal searches).…”
Section: Estimated Cost and Sensitivitymentioning
confidence: 99%
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“…A number of all-sky searches have been carried out on initial LIGO data, [2][3][4][5][6][7][8][9][10][11][12][13][14][15], of which [2,3,7,9,14] also ran on Einstein@Home. Einstein@Home is a distributed computing project which uses the idle time of computers volunteered by the general public to search for GWs.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, the computational cost of a naive implementation of a matched filtered search would be formidable. For example if we were to conduct a one stage match-filtered search on the MLDC 1B dataset to get parameter accuracies to similar levels to those we quote in our results section we estimate that you would require 10 19 templates. Of course detecting a signal as loud as the ones used in the MLDC requires significantly less templates, and can be done by placing templates in mass space only.…”
Section: Introductionmentioning
confidence: 84%