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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Data from current gravitational wave detectors contains a high rate oftransient noise (glitches) that can trigger false detections and obscure trueastrophysical events. Existing noise-detection algorithms largely rely onmodel-based methods that may miss noise transients unwitnessed by auxiliarysensors or with exotic morphologies. We propose the Unicorn Multi-windowAnomaly-detection Pipeline (UniMAP): a model-free algorithm to identify andcharacterize transient noise leveraging the Temporal Outlier Factor (TOF) via amulti-window data-resampling scheme. We show this windowing scheme extends theanomaly detection capabilities of the TOF algorithm to resolve noise transientsof arbitrary morphology and duration. We demonstrate the efficacy of thispipeline in detecting glitches during LIGO and Virgo's third observing run, anddiscuss potential applications.

UniMAP: Model-free detection of unclassified noise transients in LIGO-Virgo data using the Temporal Outlier Factor