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تسجيل مستخدم جديدLow latency search for compact binary coalescences using MBTA
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T. Adams
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The Multi-Band Template Analysis is a low-latency analysis pipeline for the detection of gravitational waves to triggering electromagnetic follow up observations. Coincident observation of gravitational waves and an electromagnetic counterpart will allow us to develop a complete picture of energetic astronomical events. We give an outline of the MBTA pipeline, as well as the procedure for distributing gravitational wave candidate events to our astronomical partners. We give some details of the recent work that has been done to improve the MBTA pipeline and are now making preparations for the advanced detector era.
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The multi-band template analysis (MBTA) pipeline is a low-latency coincident analysis pipeline for the detection of gravitational waves (GWs) from compact binary coalescences. MBTA runs with a low computational cost, and can identify candidate GW eve
nts online with a sub-minute latency. The low computational running cost of MBTA also makes it useful for data quality studies. Events detected by MBTA online can be used to alert astronomical partners for electromagnetic follow-up. We outline the current status of MBTA and give details of recent pipeline upgrades and validation tests that were performed in preparation for the first advanced detector observing period. The MBTA pipeline is ready for the outset of the advanced detector era and the exciting prospects it will bring.
We describe the Multi-Band Template Analysis (MBTA) search for gravitational waves signals from coalescences of compact objects in the LIGO-Virgo data, at the time of the third observing run (2019-2020), both for low-latency detections and for offlin
e analysis. Details are given on the architecture and functioning of the pipeline, including transient noise mitigation strategies, parameter space for the searched signals, detection of candidates and evaluation of a false alarm rate associated to them. The performance of the low-latency search is demonstrated based on the LIGO-Virgo third observing run, during which MBTA has contributed to 42 alerts, submitting candidates with a median latency of 36 seconds. The performance of the offline search is illustrated on a subset of data collected during the second LIGO-Virgo observation run in 2017, and are quantified based on injections of simulated signal events on the same data.
The first observing run of Advanced LIGO spanned 4 months, from September 12, 2015 to January 19, 2016, during which gravitational waves were directly detected from two binary black hole systems, namely GW150914 and GW151226. Confident detection of g
ravitational waves requires an understanding of instrumental transients and artifacts that can reduce the sensitivity of a search. Studies of the quality of the detector data yield insights into the cause of instrumental artifacts and data quality vetoes specific to a search are produced to mitigate the effects of problematic data. In this paper, the systematic removal of noisy data from analysis time is shown to improve the sensitivity of searches for compact binary coalescences. The output of the PyCBC pipeline, which is a python-based code package used to search for gravitational wave signals from compact binary coalescences, is used as a metric for improvement. GW150914 was a loud enough signal that removing noisy data did not improve its significance. However, the removal of data with excess noise decreased the false alarm rate of GW151226 by more than two orders of magnitude, from 1 in 770 years to less than 1 in 186000 years.
This paper presents the 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 th
is 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 for each sky direction. 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-Virgos second observation run. We demonstrate that the median latency of the SPIIR pipeline is less than 9 seconds, and present an achievable roadmap to reduce the latency to less than 5 seconds. During the O3 online run, SPIIR registered triggers associated with 38 of the 56 non-retracted 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.
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 hole binary
mergers, GW150914 and GW151226. At its core, the PyCBC search performs a matched-filter search for binary merger signals using a bank of gravitational-wave template waveforms. We provide a complete description of the search pipeline including the steps used to mitigate the effects of noise transients in the data, identify candidate events and measure their statistical significance. The analysis is able to measure false-alarm rates as low as one per million years, required for confident detection of signals. Using data from initial LIGOs sixth science run, we show that the new analysis reduces the background noise in the search, giving a 30% increase in sensitive volume for binary neutron star systems over previous searches.
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