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This paper presents the Summed Parallel Infinite Impulse Response (SPIIR) pipeline used for public alerts during the third advanced LIGO and Virgo observation run (O3 run). The SPIIR pipeline uses infinite impulse response (IIR) filters to perform extremely low-latency matched filtering and this process is further accelerated with graphics processing units (GPUs). It is the first online pipeline to select candidates from multiple detectors using a coherent statistic based on the maximum network likelihood ratio statistic principle. Here we simplify the derivation of this statistic using the singular-value-decomposition (SVD) technique and show that single-detector signal-to-noise ratios from matched filtering can be directly used to construct the statistic. Coherent searches are in general more computationally challenging than coincidence searches due to extra search over sky direction parameters. The search over sky directions follows an embarrassing parallelization paradigm and has been accelerated using GPUs. The detection performance is reported using a segment of public data from LIGO-Virgo’s second observation run. We demonstrate that the median latency of the SPIIR pipeline is less than 9 seconds, and present an achievable road map to reduce the latency to less than 5 seconds. During the O3 online run, SPIIR registered triggers associated with 38 of the 56 nonretracted public alerts. The extreme low-latency nature makes it a competitive choice for joint time-domain observations, and offers the tantalizing possibility of making public alerts prior to the merger phase of binary coalescence systems involving at least one neutron star.
|Number of pages||17|
|Journal||Physical Review D|
|Publication status||Published - 15 Jan 2022|
FingerprintDive into the research topics of 'SPIIR online coherent pipeline to search for gravitational waves from compact binary coalescences'. Together they form a unique fingerprint.
- 1 Active
ARC Centre of Excellence for Gravitational Wave Discovery
Bailes, M., McClelland, D. E., Levin, Y., Blair, D., Scott, S., Ottaway, D., Melatos, A., Veitch, P., Wen, L., Zhao, C., Ju, L. & Coward, D.
1/01/17 → 31/12/23
- 11 Citations
- 1 Doctoral Thesis
Pre-merger Detection and Early Warnings of Gravitational Waves from Compact Binary MergersKovalam, M., 2022, (Unpublished)
Research output: Thesis › Doctoral ThesisFile23 Downloads (Pure)