相关论文: Scalable matched-filtering pipeline for gravitatio…
We present SGNL, a scalable, low-latency gravitational-wave search pipeline. It reimplements the core matched-filtering principles of the GstLAL pipeline within a modernized framework. The Streaming Graph Navigator library, a lightweight…
GstLAL is a stream-based matched-filtering search pipeline aiming at the prompt discovery of gravitational waves from compact binary coalescences such as the mergers of black holes and neutron stars. Over the past three observation runs by…
The GstLAL library, derived from Gstreamer and the LIGO Algorithm Library, supports a stream-based approach to gravitational-wave data processing. Although GstLAL was primarily designed to search for gravitational-wave signatures of merging…
We report a novel application of graphics processing units (GPUs) for the purpose of accelerating the search pipelines for gravitational waves from coalescing binaries of compact objects. A speed-up of 16 fold has been achieved compared…
This paper introduces significant improvements to the GravAD pipeline, a Python-based system for gravitational wave detection. These advancements include a reduction in waveform templates, implementation of simulated signals, and…
In this work, we present new methods implemented in the GstLAL offline gravitational wave search. These include a technique to reuse the matched filtering data products from a GstLAL online analysis, which hugely reduces the time and…
Searches for gravitational waves from compact binary coalescences employ a process called matched filtering, in which gravitational wave strain data is cross-correlated against a bank of waveform templates. Data from every observing run of…
Low-latency detections of gravitational waves (GWs) are crucial to enable prompt follow-up observations to astrophysical transients by conventional telescopes. We have developed a low-latency pipeline using a technique called Summed…
Matched-filtering gravitational wave search pipelines identify gravitational wave signals by computing correlations, i.e., signal-to-noise ratios, between gravitational wave detector data and gravitational wave template waveforms. Intrinsic…
We demonstrate the implementation of a sensitive search pipeline for gravitational waves from coalescing binary black holes whose components have spins aligned with the orbital angular momentum. We study the pipeline recovery of simulated…
Searching for gravitational waves from compact binary coalescence (CBC) is performed by matched filtering the observed strain data from gravitational-wave observatories against a discrete set of waveform templates designed to accurately…
After their successful first observing run (September 12, 2015 - January 12, 2016), the Advanced LIGO detectors were upgraded to increase their sensitivity for the second observing run (November 30, 2016 - August 26, 2017). The Advanced…
Gravitational wave searches rely on a combination of methods, including matched filtering, coherent analyses, and more recent machine learning based pipelines. For compact binary coalescences, where signals originate from the relativistic…
Gravitational-wave signals from compact binary coalescences are most efficiently identified through matched filter searches, which match the data against a pre-generated bank of gravitational-wave templates. Although different techniques…
As the number of confident gravitational-wave detections grows, population-level hierarchical analyses face increasing computational costs. Dark-siren cosmological inference integrates over the localisation volume of each gravitational-wave…
Searching for gravitational waves from stellar-mass binary black holes with LISA remains a challenging open problem. Conventional template-bank approaches to the search are impossible due to the prohibitive number of templates that would be…
We describe the PyCBC search for gravitational waves from compact-object binary coalescences in advanced gravitational-wave detector data. The search was used in the first Advanced LIGO observing run and unambiguously identified two black…
Gravitational-wave data from advanced-era interferometric detectors consists of background Gaussian noise, frequent transient artefacts, and rare astrophysical signals. Multiple search algorithms exist to detect the signals from compact…
In hierarchical searches for continuous gravitational waves, clustering of candidates is an important postprocessing step because it reduces the number of noise candidates that are followed-up at successive stages [1][7][12]. Previous…
In this paper we report the prototype of the first coalescing binary detection pipeline fully implemented on NVIDIA GPU hardware accelerators. The code has been embedded in a GPU library, called cuInspiral and has been developed under CUDA…