Supplement: "Localization and broadband follow-up of the gravitational-wave transient GW150914" (2016, ApJL, 826, L13)

This Supplement provides supporting material for Abbott et al. (2016a). We briefly summarize past electromagnetic (EM) follow-up efforts as well as the organization and policy of the current EM follow-up program. We compare the four probability sky maps produced for the gravitational-wave transient GW150914, and provide additional details of the EM follow-up observations that were performed in the different bands

Localization and broadband follow-up of the gravitational-wave transient GW150914

A gravitational-wave (GW) transient was identified in data recorded by the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) detectors on 2015 September 14. The event, initially designated G184098 and later given the name GW150914, is described in detail elsewhere. By prior arrangement, preliminary estimates of the time, significance, and sky location of the event were shared with 63 teams of observers covering radio, optical, near-infrared, X-ray, and gamma-ray wavelengths with ground- and space-based facilities. In this Letter we describe the low-latency analysis of the GW data and present the sky localization of the first observed compact binary merger. We summarize the follow-up observations reported by 25 teams via private Gamma-ray Coordinates Network circulars, giving an overview of the participating facilities, the GW sky localization coverage, the timeline, and depth of the observations. As this event turned out to be a binary black hole merger, there is little expectation of a detectable electromagnetic (EM) signature. Nevertheless, this first broadband campaign to search for a counterpart of an Advanced LIGO source represents a milestone and highlights the broad capabilities of the transient astronomy community and the observing strategies that have been developed to pursue neutron star binary merger events. Detailed investigations of the EM data and results of the EM follow-up campaign are being disseminated in papers by the individual teams

Localization and Broadband Follow-up of the Gravitational-wave Transient GW150914

A gravitational-wave (GW) transient was identified in data recorded by the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) detectors on 2015 September 14. The event, initially designated G184098 and later given the name GW150914, is described in detail elsewhere. By prior arrangement, preliminary estimates of the time, significance, and sky location of the event were shared with 63 teams of observers covering radio, optical, near-infrared, X-ray, and gamma-ray wavelengths with ground- and space-based facilities. In this Letter we describe the low-latency analysis of the GW data and present the sky localization of the first observed compact binary merger. We summarize the follow-up observations reported by 25 teams via private Gamma-ray Coordinates Network circulars, giving an overview of the participating facilities, the GW sky localization coverage, the timeline, and depth of the observations. As this event turned out to be a binary black hole merger, there is little expectation of a detectable electromagnetic (EM) signature. Nevertheless, this first broadband campaign to search for a counterpart of an Advanced LIGO source represents a milestone and highlights the broad capabilities of the transient astronomy community and the observing strategies that have been developed to pursue neutron star binary merger events. Detailed investigations of the EM data and results of the EM follow-up campaign are being disseminated in papers by the individual teams. </p

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Localization and broadband follow-up of the gravitational-wave transient GW150914

A gravitational-wave transient was identified in data recorded by the Advanced LIGO detectors on 2015 September 14. The event candidate, initially designated G184098 and later given the name GW150914, is described in detail elsewhere. By prior arrangement, preliminary estimates of the time, significance, and sky location of the event were shared with 63 teams of observers covering radio, optical, near-infrared, X-ray, and gamma-ray wavelengths with ground- and space-based facilities. In this Letter we describe the low-latency analysis of the gravitational wave data and present the sky localization of the first observed compact binary merger. We summarize the follow-up observations reported by 25 teams via private Gamma-ray Coordinates Network Circulars, giving an overview of the participating facilities, the gravitational wave sky localization coverage, the timeline and depth of the observations. As this event turned out to be a binary black hole merger, there is little expectation of a detectable electromagnetic signature. Nevertheless, this first broadband campaign to search for a counterpart of an Advanced LIGO source represents a milestone and highlights the broad capabilities of the transient astronomy community and the observing strategies that have been developed to pursue neutron star binary merger events. Detailed investigations of the electromagnetic data and results of the electromagnetic follow-up campaign will be disseminated in the papers of the individual teams

The Hitchhiker's guide to nonlinear filtering

ISSN:0022-249

Asymptotically exact unweighted particle filter for manifold-valued hidden states and point process observations

The filtering of a Markov diffusion process on a manifold from counting process observations leads to ‘large’ changes in the conditional distribution upon an observed event, corresponding to a multiplication of the density by the intensity function of the observation process. If that distribution is represented by unweighted samples or particles, they need to be jointly transformed such that they sample from the modified distribution. In previous work, this transformation has been approximated by a translation of all the particles by a common vector. However, such an operation is ill-defined on a manifold, and on a vector space, a constant gain can lead to a wrong estimate of the uncertainty over the hidden state. Here, taking inspiration from the feedback particle filter (FPF), we derive an asymptotically exact filter (called ppFPF) for point process observations, whose particles evolve according to intrinsic (i.e., parametrization-invariant) dynamics that are composed of the dynamics of the hidden state plus additional control terms. While not sharing the gain-times-error structure of the FPF, the optimal control terms are expressed as solutions to partial differential equations analogous to the weighted Poisson equation for the gain of the FPF. The proposed filter can therefore make use of existing approximation algorithms for solutions of weighted Poisson equations.ISSN:2475-145

Approximating the Predictive Distribution via Adversarially-Trained Hypernetworks

Being able to model uncertainty is a vital property for any intelligent agent. In an environment in which the domain of input stimuli is fully controlled neglecting uncertainty may work, but this usually does not hold true for any real-world scenario. This highlights the necessity for learning algorithms that robustly detect noisy and out-of-distribution examples. Here we propose a novel approach for uncertainty estimation based on adversarially trained hypernetworks. We define a weight posterior to uniformly allow weight realizations of a neural network that meet a chosen fidelity constraint. This setting gives rise to a posterior predictive distribution that allows inference on unseen data samples. In this work, we train a combination of hypernetwork and main network via the GAN framework by sampling from this posterior predictive distribution. Due to the indirect training of the hypernetwork our method does not suffer from complicated loss formulations over weight configurations. We report empirical results that show that our method is able to capture uncertainty over outputs and exhibits performance that is on par with previous work. Furthermore, the use of hypernetworks allows producing arbitrarily complex, multi-modal weight posteriors

Smartphone distraction during nursing care. Systematic literature review

Aim: To investigate the impact of smartphone distraction on the quality and safety of care provided by the nursing population during work. Background: About 80% of nurses use the smartphone in the workplace both for personal purposes and as a useful support to improve the quality of care. Distraction from smartphones during care is a phenomenon that should be known and managed within each health service. Methods: A systematic review of the literature was conducted using the PRISMA methodology. The sources included in the review study were subjected to a qualitative assessment using the GRADE method. Results: Sixteen articles were included in the review. Studies included highlight the positive and negative consequences of using mobile devices during nursing practice. Findings identify the smartphone as a generator of stimuli capable of diverting the attention of the person from the priority activities and absorbing the cognitive resources useful for carrying out these activities. Some studies aimed to show the restriction policies and/or the strategies for reducing disruptions. This review highlights how the free and indiscriminate use of the smartphone can negatively affect patient safety and the nurse-patient relationship through the dehumanization and depersonalization of care. Conclusions: Mobile technology can improve nurses' performance and the quality of care provided. However, the application of regulations and policies by healthcare facilities is desirable to avoid inappropriate use of these devices by nurses. The available data do not provide a precise estimate of the effect that distraction from smartphones has on the outcomes of nursing care