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Register a new userImplementing a semicoherent search for continuous gravitational waves using optimally-constructed template banks
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All-sky surveys for isolated continuous gravitational waves present a significant data-analysis challenge. Semicoherent search methods are commonly used to efficiently perform the computationally-intensive task of searching for these weak signals in the noisy data of gravitational-wave detectors such as LIGO and Virgo. We present a new implementation of a semicoherent search method, Weave, that for the first time makes full use of a parameter-space metric to generate banks of search templates at the correct resolution, combined with optimal lattices to minimize the required number of templates and hence the computational cost of the search. We describe the implementation of Weave and associated design choices, and characterize its behavior using semi-analytic models.
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Isolated neutron stars are prime targets for continuous-wave (CW) searches by ground-based gravitational$-$wave interferometers. Results are presented from a CW search targeting ten pulsars. The search uses a semicoherent algorithm, which combines the maximum-likelihood $mathcal{F}$-statistic with a hidden Markov model (HMM) to efficiently detect and track quasi$-$monochromatic signals which wander randomly in frequency. The targets, which are associated with TeV sources detected by the High Energy Stereoscopic System (H.E.S.S.), are chosen to test for gravitational radiation from young, energetic pulsars with strong $mathrm{gamma}$-ray emission, and take maximum advantage of the frequency tracking capabilities of HMM compared to other CW search algorithms. The search uses data from the second observing run of the Advanced Laser Interferometer Gravitational-Wave Observatory (aLIGO). It scans 1$-$Hz sub-bands around $f_*$, 4$f_*$/3, and 2$f_*$, where $f_*$ denotes the stars rotation frequency, in order to accommodate a physically plausible frequency mismatch between the electromagnetic and gravitational-wave emission. The 24 sub-bands searched in this study return 5,256 candidates above the Gaussian threshold with a false alarm probability of 1$%$ per sub-band per target. Only 12 candidates survive the three data quality vetoes which are applied to separate non$-$Gaussian artifacts from true astrophysical signals. CW searches using the data from subsequent observing runs will clarify the status of the remaining candidates.
We present an improved method of targeting continuous gravitational-wave signals in data from the LIGO and Virgo detectors with a higher efficiency than the time-domain Bayesian pipeline used in many previous searches. Our spectral interpolation algorithm, SplInter, removes the intrinsic phase evolution of the signal from source rotation and relative detector motion. We do this in the frequency domain and generate a time series containing only variations in the signal due to the antenna pattern. Although less flexible than the classic heterodyne approach, SplInter allows for rapid analysis of putative signals from isolated (and some binary) pulsars, and efficient follow-up searches for candidate signals generated by other search methods. The computational saving over the heterodyne approach can be many orders of magnitude, up to a factor of around fifty thousand in some cases, with a minimal impact on overall sensitivity for most targets.
We present results of an all-sky search for continuous gravitational waves (CWs), which can be produced by fast-spinning neutron stars with an asymmetry around their rotation axis, using data from the second observing run of the Advanced LIGO detectors. We employ three different semi-coherent methods ($textit{FrequencyHough}$, $textit{SkyHough}$, and $textit{Time-Domain $mathcal{F}$-statistic}$) to search in a gravitational-wave frequency band from 20 to 1922 Hz and a first frequency derivative from $-1times10^{-8}$ to $2times10^{-9}$ Hz/s. None of these searches has found clear evidence for a CW signal, so we present upper limits on the gravitational-wave strain amplitude $h_0$ (the lowest upper limit on $h_0$ is $1.7times10^{-25}$ in the 123-124 Hz region) and discuss the astrophysical implications of this result. This is the most sensitive search ever performed over the broad range of parameters explored in this study.
We present the results of a search in LIGO O2 public data for continuous gravitational waves from the neutron star in the low-mass X-ray binary Scorpius X-1. We search for signals with $approx$ constant frequency in the range 40-180 Hz. Thanks to the efficiency of our search pipeline we can use a long coherence time and achieve unprecedented sensitivity, significantly improving on existing results. This is the first search that has been able to probe gravitational wave amplitudes that could balance the accretion torque at the neutron star radius. Our search excludes emission at this level between 67.5 Hz and 131.5 Hz, for an inclination angle $44^circ pm 6^circ$ derived from radio observations (Fomalont et al. 2001), and assuming that the spin axis is perpendicular to the orbital plane. If the torque arm is $approx $ 26 km -- a conservative estimate of the alfven radius -- our results are more constraining than the indirect limit across the band. This allows us to exclude certain mass-radius combinations and to place upper limits on the strength of the stars magnetic field. We also correct a mistake that appears in the literature in the equation that gives the gravitational wave amplitude at the torque balance (Abbott et al. 2017b, 2019a) and we re-interpret the associated latest LIGO/Virgo results in light of this.
Many continuous gravitational wave searches are affected by instrumental spectral lines that could be confused with a continuous astrophysical signal. Several techniques have been developed to limit the effect of these lines by penalising signals that appear in only a single detector. We have developed a general method, using a convolutional neural network, to reduce the impact of instrumental artefacts on searches that use the SOAP algorithm. The method can identify features in corresponding frequency bands of each detector and classify these bands as containing a signal, an instrumental line, or noise. We tested the method against four different data-sets: Gaussian noise with time gaps, data from the final run of Initial LIGO (S6) with signals added, the reference S6 mock data challenge data set and signals injected into data from the second advanced LIGO observing run (O2). Using the S6 mock data challenge data set and at a 1% false alarm probability we showed that at 95% efficiency a fully-automated SOAP search has a sensitivity corresponding to a coherent signal-to-noise ratio of 110, equivalent to a sensitivity depth of 10 Hz$^{-1/2}$, making this automated search competitive with other searches requiring significantly more computing resources and human intervention.
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