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Searches for continuous gravitational waves in the advanced detector era
Ra Inta (Texas Tech University) for the LIGO Scientific Collaboration and the Virgo Collaboration LIGO Document G v4
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No Continuous gravitational Waves (CW) detected… yet!
Most searches begin after an observing run has ended Still analysing LIGO O1 data
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CW Sources LIGO/Virgo band: O(10) Hz – O(1) kHz
Rotating neutron stars with some non-axisymmetry Axions?
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Animation: Joeri van Leeuwen
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Triaxial model
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Deviation from axisymmetry: ellipticity
Determines maximum height of ‘hills’ supported within NS crust ( O(few) cm )
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Expected amplitudes
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Expected amplitudes Abbott, B.P. et al., PRL 116:061102 (2016)
Caltech/MIT/LIGO Lab Abbott, B.P. et al., PRL 116: (2016)
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Expected amplitudes
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Fluid modes r-mode instability B. Owen/C. Hanna
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Precession (plus side-bands) M. Kramer
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Neutron star population
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Neutron star population
Where are the other ~108 neutron stars?
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aLIGO sensitivity ~17% of (known) pulsars ~23% of (known) pulsars
B.P. Abbott et al., PRL 116: (2016)
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Computational bound Averaging means most CW searches are computationally limited e.g.: typical, modest, search takes ~400,000 CPU hrs on Albert Einstein Institute’s Atlas supercomputer Bounds often explicitly used to determine a figure of merit for CW searches
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What if we make a detection?
Follow-up with multiple search pipelines Compare GW phase to EM pulse timing Potential for EM follow-up Potential confirmation of many neutron star properties Test General Relativity Constrain neutron star equation of state
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D. Page
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Adapted from Horowitz, C.J. and Kadau, K., PRL 102:191102 (2009)
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Types of CW searches
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1) Targeted searches What we know: α, δ, f0, df/dt
Searches can be narrow-band around parameters Three pipelines NASA/ESA/J. Hester/A Loll
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1) Targeted searches Crab Vela Meaningful limits on Vela and Crab
Good prospects for aLIGO! Aasi, J et al., ApJ. 785:119 (2014)
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1) Targeted searches Narrow-band around parameters of Crab and Vela
Robust w.r.t to model assumptions Looked at five partial harmonics per target Meaningful upper limits set on both: 0.50 and 0.97 expected (spin-down) h0 respectively Aasi, J. et al., PRD 91: (2015)
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2) Directed searches What we know: α, δ
Search over: f0, df/dt, d2f/dt2, … NASA/Chandra/STScI/Spitzer
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2) Directed searches Young supernova remnants
Adapted from NASA/JPL-Caltech/ESO/R. Hurt., with permission Aasi, J. et al. ApJ. 813(1) 39 (2015)
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2) Directed searches Beat age-based upper limit on nine supernova remnants Constraints on r-mode amplitudes Many more targets in O1 Aasi, J. et al. ApJ. 813(1) 39 (2015)
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Sco-X1 Sco-X1 Mock Data Challenge J.T. Whelan’s talk Y. Zhang’s talk
G. Meadors’ poster Sco-X1 Mock Data Challenge Aasi, J. et al., PRD 91: (2015) Messenger, C. et al., PRD 92: (2015)
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3) All-sky searches What we know: - Search over: α, δ, f0, df/dt, …
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3) All-sky searches Low frequency all-sky (frequency Hough) --- Virgo
Virgo VSR2 and VSR4 data Hierarchical Hough-transform in frequency domain Best upper limits below 80 Hz Aasi, J. et al., PRD 93: (2016)
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3) All-sky searches PowerFlux (S6)
Most comprehensive coverage of parameter space to date Uses distribution-free ‘universal statistic’ to reduce impact of non-Gaussian noise ‘Loosely coherent’ follow-up arXiv:
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3) All-sky searches: binaries
TwoSpect Polynomial Aasi, J. et al., PRD 90: (2014)
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3) All Some-sky searches
Loosely coherent search in Orion's Spur Deeper search in small patch of sky Multiple stages of increasing coherence Identified 70 candidates Three most significant ruled out by other pipelines Aasi, J. et al., PRD 93: (2016)
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Pipeline optimisation and improvements
Directed search optimisations -- J. Ming’s talk Parameter space improvements -- Wette, K., PRD 92: (2015); Jones, D.I., MNRAS 453:53 (2015); Leaci, P., and Prix, R., PRD 91: (2015) Searches for time-limited CWs -- Keitel, D., arXiv: Semi-coherent all-sky improvements -- Goetz, E. and Riles, K., CQG 33: (2016) Non-GR alternatives -- Isi, M. et al., PRD 91: (2015) -- see M. Isi’s poster Many more!
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Summary and the future Many improvements made to search pipelines
Increasingly better upper limits and parameter space coverage No detection… yet The future looks bright!
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How can you get involved?
A. Singh’s talk
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