TY - JOUR
T1 - Second Einstein Telescope mock data and science challenge
T2 - Low frequency binary neutron star data analysis
AU - Meacher, Duncan
AU - Cannon, Kipp
AU - Hanna, Chad
AU - Regimbau, Tania
AU - Sathyaprakash, B. S.
N1 - Funding Information:
We thank Bruce Allen and the Albert Einstein Institute in Hannover, supported by the Max-Planck-Gesellschaft, for use of the Atlas high-performance computing cluster in the data generation and analysis, and Carsten Aulbert for technical advice and assistance. D. M. acknowledges the PhD financial support from the Observatoire de la Côte dAzur and the PACA region and would also like to thank Cardiff university for funding under which part of this work was conducted. C. H. is supported by NSF grant PHY-1454389. B. S. S. acknowledges the support of the LIGO Visitor Program through the National Science Foundation award PHY-0757058, Max-Planck Institute of Gravitational Physics, Potsdam, Germany, and STFC grant ST/J000345/1.
Funding Information:
We thank Bruce Allen and the Albert Einstein Institute in Hannover, supported by the Max-Planck-Gesellschaft, for use of the Atlas high-performance computing cluster in the data generation and analysis, and Carsten Aulbert for technical advice and assistance. D. M. acknowledges the PhD financial support from the Observatoire de la C?te dAzur and the PACA region and would also like to thank Cardiff university for funding under which part of this work was conducted. C. H. is supported by NSF grant PHY-1454389. B. S. S. acknowledges the support of the LIGO Visitor Program through the National Science Foundation award PHY-0757058, Max-Planck Institute of Gravitational Physics, Potsdam, Germany, and STFC grant ST/J000345/1.
Publisher Copyright:
© 2016 American Physical Society.
PY - 2016/1/11
Y1 - 2016/1/11
N2 - The Einstein Telescope is a conceived third-generation gravitational-wave detector that is envisioned to be an order of magnitude more sensitive than advanced LIGO, Virgo, and Kagra, which would be able to detect gravitational-wave signals from the coalescence of compact objects with waveforms starting as low as 1 Hz. With this level of sensitivity, we expect to detect sources at cosmological distances. In this paper we introduce an improved method for the generation of mock data and analyze it with a new low-latency compact binary search pipeline called gstlal. We present the results from this analysis with a focus on low-frequency analysis of binary neutron stars. Despite compact binary coalescence signals lasting hours in the Einstein Telescope sensitivity band when starting at 5 Hz, we show that we are able to discern various overlapping signals from one another. We also determine the detection efficiency for each of the analysis runs conducted and show a proof of concept method for estimating the number signals as a function of redshift. Finally, we show that our ability to recover the signal parameters has improved by an order of magnitude when compared to the results of the first mock data and science challenge. For binary neutron stars we are able to recover the total mass and chirp mass to within 0.5% and 0.05%, respectively.
AB - The Einstein Telescope is a conceived third-generation gravitational-wave detector that is envisioned to be an order of magnitude more sensitive than advanced LIGO, Virgo, and Kagra, which would be able to detect gravitational-wave signals from the coalescence of compact objects with waveforms starting as low as 1 Hz. With this level of sensitivity, we expect to detect sources at cosmological distances. In this paper we introduce an improved method for the generation of mock data and analyze it with a new low-latency compact binary search pipeline called gstlal. We present the results from this analysis with a focus on low-frequency analysis of binary neutron stars. Despite compact binary coalescence signals lasting hours in the Einstein Telescope sensitivity band when starting at 5 Hz, we show that we are able to discern various overlapping signals from one another. We also determine the detection efficiency for each of the analysis runs conducted and show a proof of concept method for estimating the number signals as a function of redshift. Finally, we show that our ability to recover the signal parameters has improved by an order of magnitude when compared to the results of the first mock data and science challenge. For binary neutron stars we are able to recover the total mass and chirp mass to within 0.5% and 0.05%, respectively.
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U2 - 10.1103/PhysRevD.93.024018
DO - 10.1103/PhysRevD.93.024018
M3 - Article
AN - SCOPUS:84955440309
VL - 93
JO - Physical Review D
JF - Physical Review D
SN - 2470-0010
IS - 2
M1 - 024018
ER -