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Register a new userA targeted spectral interpolation algorithm for the detection of continuous gravitational waves
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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.
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A second generation of gravitational wave detectors will soon come online with the objective of measuring for the first time the tiny gravitational signal from the coalescence of black hole and/or neutron star binaries. In this communication, we propose a new time-frequency search method alternative to matched filtering techniques that are usually employed to detect this signal. This method relies on a graph that encodes the time evolution of the signal and its variability by establishing links between coefficients in the multi-scale time-frequency decomposition of the data. We provide a proof of concept for this approach.
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.
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.
We describe detection methods for extensions of gravitational wave searches to sub-solar mass compact binaries. Sub-solar mass searches were previously carried out using Initial LIGO, and Advanced LIGO boasts a detection volume approximately 1000 times bigger than Initial LIGO at design sensitivity. Low masses present computational difficulties, and we suggest a way to rein in the increase while retaining a sensitivity much greater than previous searches. Sub-solar mass compact objects are of particular interest because they are not expected to form astrophysically. If detected they could be evidence of primordial black holes (PBH). We consider a particular model of PBH binary formation that would allow LIGO/Virgo to place constraints on this population within the context of dark matter, and we demonstrate how to obtain conservative bounds for the upper limit on the dark matter fraction.
Gravitational wave searches for continuous-wave signals from neutron stars are especially challenging when the stars spin frequency is unknown a priori from electromagnetic observations and wanders stochastically under the action of internal (e.g. superfluid or magnetospheric) or external (e.g. accretion) torques. It is shown that frequency tracking by hidden Markov model (HMM) methods can be combined with existing maximum likelihood coherent matched filters like the F-statistic to surmount some of the challenges raised by spin wandering. Specifically it is found that, for an isolated, biaxial rotor whose spin frequency walks randomly, HMM tracking of the F-statistic output from coherent segments with duration T_drift = 10d over a total observation time of T_obs = 1yr can detect signals with wave strains h0 > 2e-26 at a noise level characteristic of the Advanced Laser Interferometer Gravitational Wave Observatory (Advanced LIGO). For a biaxial rotor with randomly walking spin in a binary orbit, whose orbital period and semi-major axis are known approximately from electromagnetic observations, HMM tracking of the Bessel-weighted F-statistic output can detect signals with h0 > 8e-26. An efficient, recursive, HMM solver based on the Viterbi algorithm is demonstrated, which requires ~10^3 CPU-hours for a typical, broadband (0.5-kHz) search for the low-mass X-ray binary Scorpius X-1, including generation of the relevant F-statistic input. In a realistic observational scenario, Viterbi tracking successfully detects 41 out of 50 synthetic signals without spin wandering in Stage I of the Scorpius X-1 Mock Data Challenge convened by the LIGO Scientific Collaboration down to a wave strain of h0 = 1.1e-25, recovering the frequency with a root-mean-square accuracy of <= 4.3e-3 Hz.
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