Analysis Framework for the Prompt Discovery of Compact Binary Mergers in Gravitational-wave Data (1604.04324v3)

Abstract: 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 pipeline's 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.

• The paper introduces a novel stream-based pipeline that leverages time-domain matched filtering to rapidly detect various compact binary mergers.
• The methodology incorporates an SVD-based template bank decomposition that reduces computational overhead and enables low-latency detection.
• The pipeline supports multimessenger astrophysics by providing prompt alerts, facilitating timely electromagnetic follow-ups, and enhancing gravitational wave research.

Overview of "Analysis Framework for the Prompt Discovery of Compact Binary Mergers in Gravitational-wave Data"

The paper authored by Cody Messick and various collaborators presents a novel stream-based analysis pipeline designed to rapidly detect gravitational waves (GWs) originating from compact binary mergers, including binary neutron stars (BNS), binary black holes (BBH), and neutron-star-black-hole (NSBH) binaries. This pipeline is developed for swift identification within approximately one minute of the signal's arrival at Earth, allowing for prompt follow-up observations by electromagnetic and neutrino observatories.

The authors detail the implementation of the GstLAL-based inspiral pipeline, which capitalizes on the GstLAL library and innovatively applies time-domain matched filtering. This approach diverges from the traditional frequency-domain methods, enhancing the agility of the detection process. Key to the pipeline’s efficiency is the use of a singular value decomposition (SVD)-based method for the decomposition of template banks, which reduces computational overhead and facilitates real-time data processing.

The paper also underscores the pipeline's ability to operate in both online and offline modes. The online mode is tailored for low-latency event detection, promptly identifying potential GW events such as GW151226, while the offline mode leverages more comprehensive data quality metrics and acausal methods to refine signal identification and post-event analysis, which proved useful in the verification of seminal detections like GW150914.

Methodology and Results

In addressing the methodology, the authors expound on several critical components:

1. Data Acquisition and Conditioning: The pipeline efficiently acquires real-time data from LIGO detectors, employing robust conditioning techniques to mitigate noise artifacts.
2. Power Spectral Density Estimation: The pipeline utilizes a median and running geometric mean approach for power spectral density (PSD) estimation, ensuring rapid and accurate convergence with reduced data latency.
3. Matched Filtering with LLOID Technique: The core of the event detection is the matched filtering process, which employs the LLOID method, a time-domain approach that decreases computational load while maximizing sensitivity through reduced orthonormal filter sets.
4. Event Identification and Ranking: Coincidence detection is employed to identify potential GW signals across multiple detectors. Events are subsequently ranked using a likelihood-ratio statistic, balancing signal versus noise probabilities.
5. Pipeline Performance: The pipeline's performance is evaluated through software injections, establishing the sensitivity and detection efficacy across a range of binary systems. The inclusion of simulated signals provides a comprehensive assessment of the pipeline’s detection sensitivity.

Implications and Future Directions

The implications of this pipeline are significant, particularly in enhancing the collaboration between gravitational wave detectors and electromagnetic observatories through rapid multimessenger astrophysics initiatives. By enabling timely alerts for electromagnetic follow-ups, the pipeline extends the possibility of detecting and studying GW counterparts, such as kilonovae associated with BNS mergers, thus aiding in the advancement of high-energy astrophysics.

The paper's insights into online and offline data processing suggest potential for future scalability and adaptability to progressively sensitive detectors, such as those in the evolving global network of third-generation observatories like the Einstein Telescope. The authors advocate for ongoing refinement of statistical models and computational techniques to bolster the robustness and timeliness of gravitational wave detection frameworks in subsequent observations and theoretical explorations.

In conclusion, this paper represents a substantial contribution to gravitational wave astronomy, offering a detailed and practical framework for the expeditious detection of compact binary mergers in gravitational-wave data. The mechanisms and results delineated pave the way for future research and operational undertakings in the domain of multimessenger astrophysics.