Gaussian Processes for Gravitational-wave Astronomy

Interferometric gravitational-wave observatories have opened a new era in astronomy. The rich data produced by an international network enables detailed analysis of the curved space-time around black holes. With nearly one hundred signals observed so far and thousands expected in the next decade, their population properties enable insights into stellar evolution and the expansion of our Universe. However, the detectors are afflicted by transient noise artefacts known as "glitches" which contaminate the signals and bias inferences. Of the 90 signals detected to date, 18 were contaminated by glitches. This feasibility study explores a new approach to transient gravitational-wave data analysis using Gaussian processes, which model the underlying physics of the glitch-generating mechanism rather than the explicit realisation of the glitch itself. We demonstrate that if the Gaussian process kernel function can adequately model the glitch morphology, we can recover the parameters of simulated signals. Moreover, we find that the Gaussian processes kernels used in this work are well-suited to modelling long-duration glitches which are most challenging for existing glitch-mitigation approaches. Finally, we show how the time-domain nature of our approach enables a new class of time-domain tests of General Relativity, performing a re-analysis of the inspiral-merger-ringdown test on the first observed binary black hole merger. Our investigation demonstrates the feasibility of the Gaussian processes as an alternative to the traditional framework but does not yet establish them as a replacement. Therefore, we conclude with an outlook on the steps needed to realise the full potential of the Gaussian process approach.Comment: 12 pages, under review by MNRA

Hierarchical multi-stage MCMC follow-up of continuous gravitational wave candidates

Leveraging Markov chain Monte Carlo (MCMC) optimization of the F-statistic, we introduce a method for the hierarchical follow-up of continuous gravitational wave candidates identified by wide-parameter space semi-coherent searches. We demonstrate parameter estimation for continuous wave sources and develop a framework and tools to understand and control the effective size of the parameter space, critical to the success of the method. Monte Carlo tests of simulated signals in noise demonstrate that this method is close to the theoretical optimal performance.Comment: 16 pages, 9 figures, 3 tables; updated following acceptance for publication in Phys. Rev.

Understanding binary neutron star collisions with hypermodels

Gravitational waves from the collision of binary neutron stars provide a unique opportunity to study the behaviour of supranuclear matter, the fundamental properties of gravity, and the cosmic history of our Universe. However, given the complexity of Einstein's Field Equations, theoretical models that enable source-property inference suffer from systematic uncertainties due to simplifying assumptions. We develop a hypermodel approach to compare and measure the uncertainty gravitational-wave approximants. Using state-of-the-art models, we apply this new technique to the binary neutron star observations GW170817 and GW190425 and the sub-threshold candidate GW200311_103121. Our analysis reveals subtle systematic differences between waveform models, and a frequency-dependence study suggests that this is due to the treatment of the tidal sector. This new technique provides a proving ground for model development, and a means to identify waveform-systematics in future observing runs where detector improvements will increase the number and clarity of binary neutron star collisions we observe.Comment: 10 pages, 5 figures, 1 table. Published Nature Astronom

Faster search for long gravitational-wave transients: GPU implementation of the transient F-statistic

The F-statistic is an established method to search for continuous gravitational waves from spinning neutron stars. Prix et al. (2011) introduced a variant for transient quasi-monochromatic signals. Possible astrophysical scenarios for such transients include glitching pulsars, newborn neutron stars and accreting systems. Here we present a new implementation of the transient F-statistic, using pyCUDA to leverage the power of modern graphics processing units (GPUs). The obtained speedup allows efficient searches over much wider parameter spaces, especially when using more realistic transient signal models including time-varying (e.g. exponentially decaying) amplitudes. Hence, it can enable comprehensive coverage of glitches in known nearby pulsars, improve the follow-up of outliers from continuous-wave searches, and might be an important ingredient for future blind all-sky searches for unknown neutron stars.Comment: 13 pages, 3 figures; v2: updated reference to 1710.02327 and its erratu

Oyster Demand Adjustments to Counter-Information and Source Treatments in Response to Vibrio vulnificus

A web-based contingent behavior analysis is developed to quantity the effect of both negative and positive information treatments and post harvest processes (PHP) on demand for oysters. Results from a panel model indicate that consumers of raw and cooked oysters behave differently after news of an oyster-related human mortality. While cooked oyster consumers take precautionary measures against risk, raw oyster consumers exhibit optimistic bias and increase their consumption level. Further, by varying the source of a counter-information treatment, we find that source credibility impacts behavior. Oyster consumers, and in particular, raw oyster consumers, are most responsive to information provided by a not-for-profit, non-governmental organization. Finally, post harvest processing of oysters has no impact on demand. Key Words: Oyster demand; consumer behavior; non-market valuation; Vibrio vulnificus; information treatments; source credibility; optimistic bias

Oyster Demand Adjustments to Counter-Information and Source Treatments in Response to Vibrio vulnificus

A web-based contingent behavior analysis was developed to quantify the effect of both negative and positive information treatments and post harvest processes on demand for oysters. Results from a panel model indicate that consumers of raw and cooked oysters behave differently after news of an oyster-related human mortality. While cooked oyster consumers take precautionary measures against risk, raw oyster consumers exhibit optimistic bias and increase their consumption level. Further, by varying the source of a counter-information treatment, we find that source credibility impacts behavior. Oyster consumers, and in particular, raw oyster consumers, are most responsive to information provided by a not-for- profit, nongovernmental organization. Finally, post harvest processing of oysters has no impact on demand.consumer behavior, information treatments, non-market valuation, optimistic bias, Oyster demand, source credibility, Vibrio vulnificus, Agribusiness, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, Institutional and Behavioral Economics, Q18, Q13, Q58,

A semicoherent glitch-robust continuous gravitational wave search

Continuous gravitational-wave signals from isolated non-axisymmetric rotating neutron stars may undergo episodic spin-up events known as glitches. If unmodelled by a search, these can result in missed or misidentified detections. We outline a semicoherent glitch-robust search method that allows identification of glitching signal candidates and inference about the model parameters.Comment: 9 pages, 6 figures, 2 table