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Register a new userOctApps: a library of Octave functions for continuous gravitational-wave data analysis
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Gravitational waves are minute ripples in spacetime, first predicted by Einsteins general theory of relativity in 1916. Gravitational waves from rapidly-rotating neutron stars, whose shape deviates from perfect axisymmetry, are a potential astrophysical source of gravitational waves, but which so far have not been detected. The search for this type of signals, also known as continuous waves, presents a significant data analysis challenge, as their weak signatures are expected to be buried deep within the instrumental noise of the LIGO and Virgo detectors. The OctApps library provides various functions, written in Octave, intended to aid research scientists who perform searches for continuous gravitational waves.
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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.
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.
This paper reviews gravitational wave sources and their detection. One of the most exciting potential sources of gravitational waves are coalescing binary black hole systems. They can occur on all mass scales and be formed in numerous ways, many of which are not understood. They are generally invisible in electromagnetic waves, and they provide opportunities for deep investigation of Einsteins general theory of relativity. Sect. 1 of this paper considers ways that binary black holes can be created in the universe, and includes the prediction that binary black hole coalescence events are likely to be the first gravitational wave sources to be detected. The next parts of this paper address the detection of chirp waveforms from coalescence events in noisy data. Such analysis is computationally intensive. Sect. 2 reviews a new and powerful method of signal detection based on the GPU-implemented summed parallel infinite impulse response filters. Such filters are intrinsically real time alorithms, that can be used to rapidly detect and localise signals. Sect. 3 of the paper reviews the use of GPU processors for rapid searching for gravitational wave bursts that can arise from black hole births and coalescences. In sect. 4 the use of GPU processors to enable fast efficient statistical significance testing of gravitational wave event candidates is reviewed. Sect. 5 of this paper addresses the method of multimessenger astronomy where the discovery of electromagnetic counterparts of gravitational wave events can be used to identify sources, understand their nature and obtain much greater science outcomes from each identified event.
We present results from searches of recent LIGO and Virgo data for continuous gravitational wave signals (CW) from spinning neutron stars and for a stochastic gravitational wave background (SGWB). The first part of the talk is devoted to CW analysis with a focus on two types of searches. In the targeted search of known neutron stars a precise knowledge of the star parameters is used to apply optimal filtering methods. In the absence of a signal detection, in a few cases, an upper limit on strain amplitude can be set that beats the spindown limit derived from attributing spin-down energy loss to the emission of gravitational waves. In contrast, blind all-sky searches are not directed at specific sources, but rather explore as large a portion of the parameter space as possible. Fully coherent methods cannot be used for these kind of searches which pose a non trivial computational challenge. The second part of the talk is focused on SGWB searches. A stochastic background of gravitational waves is expected to be produced by the superposition of many incoherent sources of cosmological or astrophysical origin. Given the random nature of this kind of signal, it is not possible to distinguish it from noise using a single detector. A typical data analysis strategy relies on cross-correlating the data from a pair or several pairs of detectors, which allows discriminating the searched signal from instrumental noise. Expected sensitivities and prospects for detection from the next generation of interferometers are also discussed for both kind of sources.
We describe a stream-based analysis pipeline to detect gravitational waves from the merger of binary neutron stars, binary black holes, and neutron-star-black-hole binaries within ~ 1 minute of the arrival of the merger signal at Earth. Such low-latency detection is crucial for the prompt response by electromagnetic facilities in order to observe any fading electromagnetic counterparts that might be produced by mergers involving at least one neutron star. Even for systems expected not to produce counterparts, low-latency analysis of the data is useful for deciding when not to point telescopes, and as feedback to observatory operations. Analysts using this pipeline were the first to identify GW151226, the second gravitational-wave event ever detected. The pipeline also operates in an offline mode, in which it incorporates more refined information about data quality and employs acausal methods that are inapplicable to the online mode. The pipelines offline mode was used in the detection of the first two gravitational-wave events, GW150914 and GW151226, as well as the identification of a third candidate, LVT151012.
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