• DOI:10.1103/PhysRevD.97.024051
• Corpus ID: 119223919

Optimally setting up directed searches for continuous gravitational waves in Advanced LIGO O1 data

@article{Ming2018OptimallySU,
  title={Optimally setting up directed searches for continuous gravitational waves in Advanced LIGO O1 data},
  author={J. Ming and Maria Alessandra Papa and Badri Krishnan and Reinhard Prix and Christian Beer and Sylvia Jiechen Zhu and Heinz-Bernd Eggenstein and Oliver Bock and Bernd Machenschalk},
  journal={Physical Review D},
  year={2018},
  volume={97},
  pages={024051}
}

• J. Ming, M. Papa, +6 authors B. Machenschalk
• Published 7 August 2017
• Physics
• Physical Review D

In this paper we design a search for continuous gravitational waves from three supernova remnants: Vela Jr., Cassiopeia A (Cas A) and G347.3. These systems might harbor rapidly rotating neutron stars emitting quasi-periodic gravitational radiation detectable by the advanced LIGO detectors. Our search is designed to use the volunteer computing project Einstein@Home for a few months and assumes the sensitivity and duty cycles of the advanced LIGO detectors during their first science run. For all three supernova remnants, the sky-positions of their central compact objects are well known but the frequency and spin-down rates of the neutron stars are unknown which makes the searches computationally limited. In a previous paper we have proposed a general framework for deciding on what target we should spend computational resources and in what proportion, what frequency and spin-down ranges we should search for every target, and with what search set-up. Here we further expand this framework and apply it to design a search directed at detecting continuous gravitational wave signals from the most promising three supernova remnants identified as such in the previous work. Our optimization procedure yields broad frequency and spin-down searches for all three objects, at an unprecedented level of sensitivity: The smallest detectable gravitational wave strain $h_0$ for Cas A is expected to be 2 times smaller than the most sensitive upper-limits published to date, and our proposed search, which was set-up and ran on the volunteer computing project Einstein@Home, covers a much larger frequency range.