English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The search for gravitational-wave signals is limited by non-Gaussiantransient noises that mimic astrophysical signals. Temporal coincidence betweentwo or more detectors is used to mitigate contamination by these instrumentalglitches. However, when a single detector is in operation, coincidence isimpossible, and other strategies have to be used. We explore the possibility ofusing neural network classifiers and present the results obtained with threetypes of architectures: convolutional neural network, temporal convolutionalnetwork, and inception time. The last two architectures are specificallydesigned to process time-series data. The classifiers are trained on a month ofdata from the LIGO Livingston detector during the first observing run (O1) toidentify data segments that include the signature of a binary black holemerger. Their performances are assessed and compared. We then apply trainedclassifiers to the remaining three months of O1 data, focusing specifically onsingle-detector times. The most promising candidate from our search is2016-01-04 12:24:17 UTC. Although we are not able to constrain the significanceof this event to the level conventionally followed in gravitational-wavesearches, we show that the signal is compatible with the merger of two blackholes with masses $m_1 = 50.7^{+10.4}_{-8.9}\,M_{\odot}$ and $m_2 =24.4^{+20.2}_{-9.3}\,M_{\odot}$ at the luminosity distance of $d_L =564^{+812}_{-338}\,\mathrm{Mpc}$.

Neural network time-series classifiers for gravitational-wave searches in single-detector periods