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Register a new userA new data analysis framework for the search of continuous gravitational wave signals
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Ornella Juliana Piccinni
Publication date
2018
fields
Physics
and research's language is
English
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Continuous gravitational wave signals, like those expected by asymmetric spinning neutron stars, are among the most promising targets for LIGO and Virgo detectors. The development of fast and robust data analysis methods is crucial to increase the chances of a detection. We have developed a new and flexible general data analysis framework for the search of this kind of signals, which allows to reduce the computational cost of the analysis by about two orders of magnitude with respect to current procedures. This can correspond, at fixed computing cost, to a sensitivity gain of up to 10%-20%, depending on the search parameter space. Some possible applications are discussed, with a particular focus on a directed search for sources in the Galactic center. Validation through the injection of artificial signals in the data of Advanced LIGO first observational science run is also shown.
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Gravitational waves in the sensitivity band of ground-based detectors can be emitted by a number of astrophysical sources, including not only binary coalescences, but also individual spinning neutron stars. The most promising signals from such sources, although not yet detected, are long-lasting, quasi-monochromatic Continuous Waves (CWs). The PyFstat package provides tools to perform a range of CW data-analysis tasks. It revolves around the F-statistic, a matched-filter detection statistic for CW signals that has been one of the standard methods for LIGO-Virgo CW searches for two decades. PyFstat is built on top of established routines in LALSuite but through its more modern Python interface it enables a flexible approach to designing new search strategies. Hence, it serves a dual function of (i) making LALSuite CW functionality more easily accessible through a Python interface, thus facilitating the new user experience and, for developers, the exploratory implementation of novel methods; and (ii) providing a set of production-ready search classes for use cases not yet covered by LALSuite itself, most notably for MCMC-based followup of promising candidates from wide-parameter-space searches.
We present a new veto procedure to distinguish between continuous gravitational wave (CW) signals and the detector artifacts that can mimic their behavior. The veto procedure exploits the fact that a long-lasting coherent disturbance is less likely than a real signal to exhibit a Doppler modulation of astrophysical origin. Therefore, in the presence of an outlier from a search, we perform a multi-step search around the frequency of the outlier with the Doppler modulation turned off (DM-off), and compare these results with the results from the original (DM-on) search. If the results from the DM-off search are more significant than those from the DM-on search, the outlier is most likely due to an artifact rather than a signal. We tune the veto procedure so that it has a very low false dismissal rate. With this veto, we are able to identify as coherent disturbances >99.9% of the 6349 candidates from the recent all-sky low-frequency Einstein@Home search on the data from the Advanced LIGO O1 observing run [1]. We present the details of each identified disturbance in the Appendix.
We present the FastEMRIWaveforms (FEW) package, a collection of tools to build and analyze extreme mass ratio inspiral (EMRI) waveforms. Here, we expand on the Physical Review Letter that introduced the first fast and accurate fully-relativistic EMRI waveform template model. We discuss the construction of the overall framework; constituent modules; and the general methods used to accelerate EMRI waveforms. Because the fully relativistic FEW model waveforms are for now limited to eccentric orbits in the Schwarzschild spacetime, we also introduce an improved Augmented Analytic Kludge (AAK) model that describes generic Kerr inspirals. Both waveform models can be accelerated using graphics processing unit (GPU) hardware. With the GPU-accelerated waveforms in hand, a variety of studies are performed including an analysis of EMRI mode content, template mismatch, and fully Bayesian Markov Chain Monte Carlo-based EMRI parameter estimation. We find relativistic EMRI waveform templates can be generated with fewer harmonic modes ($sim10-100$) without biasing signal extraction. However, we show for the first time that extraction of a relativistic injection with semi-relativistic amplitudes can lead to strong bias and anomalous structure in the posterior distribution for certain regions of parameter space.
It is well known that matched filtering techniques cannot be applied for searching extensive parameter space volumes for continuous gravitational wave signals. This is the reason why alternative strategies are being pursued. Hierarchical strategies are best at investigating a large parameter space when there exist computational power constraints. Algorithms of this kind are being implemented by all the groups that are developing software for analyzing the data of the gravitational wave detectors that will come online in the next years. In this talk we will report about the hierarchical Hough transform method that the GEO 600 data analysis team at the Albert Einstein Institute is developing. The three step hierarchical algorithm has been described elsewhere. In this talk we will focus on some of the implementational aspects we are currently concerned with.
Searches for continuous gravitational waves from unknown sources attempt to detect long-lasting gravitational radiation by identifying Doppler-modulated signatures in the data. Semicoherent methods allow for wide parameter space surveys, identifying interesting regions to be followed up using more sensitive (and computationally expensive) tools. Thus, it is required to properly understand the parameter space structure under study, as failing to do so could significantly affect the effectiveness of said strategies. We introduce a new measure for distances in parameter space suited for semicoherent continuous wave searches. This novel approach, based on comparing time-frequency tracks, can be applied to any kind of quasi-monochromatic continuous wave signals and adapts itself to the underlying structure of the parameter space under study. In a first application to the post-processing stage of an all-sky search for continuous waves from neutron stars in binary systems, we demonstrate a search sensitivity improvement by solely replacing previous ad hoc distance measures in the candidate clustering procedure by the new proposal.
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