How to search for gravitational waves from $r$-modes of known pulsars. (arXiv:1907.04946v1 [gr-qc])

<a href="http://arxiv.org/find/gr-qc/1/au:+Caride_S/0/1/0/all/0/1">Santiago Caride</a>, <a href="http://arxiv.org/find/gr-qc/1/au:+Inta_R/0/1/0/all/0/1">Ra Inta</a>, <a href="http://arxiv.org/find/gr-qc/1/au:+Owen_B/0/1/0/all/0/1">Benjamin J. Owen</a>, <a href="http://arxiv.org/find/gr-qc/1/au:+Rajbhandari_B/0/1/0/all/0/1">Binod Rajbhandari</a> (Texas Tech University)

Searches for continuous gravitational waves from known pulsars so far have

been targeted at or near the spin frequency or double the spin frequency of

each pulsar, appropriate for mass quadrupole emission. But some neutron stars

might radiate strongly through current quadrupoles via $r$-modes, which

oscillate at about four thirds the spin frequency. We show for the first time

how to construct searches over appropriate ranges of frequencies and spin-down

parameters to target $r$-modes from known pulsars. We estimate computational

costs and sensitivities of realistic $r$-mode searches using the coherent

$mathcal{F}$-statistic, and find that feasible searches for known pulsars can

beat spin-down limits on gravitational wave emission even with existing LIGO

and Virgo data.

Searches for continuous gravitational waves from known pulsars so far have

been targeted at or near the spin frequency or double the spin frequency of

each pulsar, appropriate for mass quadrupole emission. But some neutron stars

might radiate strongly through current quadrupoles via $r$-modes, which

oscillate at about four thirds the spin frequency. We show for the first time

how to construct searches over appropriate ranges of frequencies and spin-down

parameters to target $r$-modes from known pulsars. We estimate computational

costs and sensitivities of realistic $r$-mode searches using the coherent

$mathcal{F}$-statistic, and find that feasible searches for known pulsars can

beat spin-down limits on gravitational wave emission even with existing LIGO

and Virgo data.

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