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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Wavelet decomposition is a method that has been applied to signal processingin a wide range of subjects. The decomposition isolates small scale features ofa signal from large scale features, while also maintaining information aboutwhere in the signal those features occur. Wavelets obey particular scalingrelations and are especially suited to the analysis of systems that areself-similar and scale invariant. They are therefore a natural tool for thestudy of hadron collisions.  This paper introduces the use of wavelets for de-noising (removal of softactivity), studying the scaling behaviour of a shower, and recognising jetsaccording to this behaviour. This is demonstrated by processing a sample ofboosted W boson Monte Carlo events together with their QCD background. Themethod is quite general and can be used as a pre-processing step in conjunctionwith any jet-finder or other event-shape algorithm. The result in this simpleexample is a significant enhancement in both the size and shape of the W bosonmass peak, together with an improved separation of the background distribution.

Wavelet Analysis: Event De-noising, Shower Evolution and Jet Substructure Without Jets