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

In phenomenological preparation for new measurements one searches for thecarriers of quality signatures. Often, the first approach quantities may bedifficult to measure or to provide sufficiently precise predictions forcomparisons.  Complexity of necessary details grow with precision. To achieve the goal onecan not break the theory principles, and take into account effects which couldbe ignored earlier. Mixed approach where dominant effects are taken intoaccount with intuitive even simplistic approach was developed.  Non dominant corrections were controlled with the help of Monte Carlosimulations.  Concept of Optimal Variables was successfully applied for many measurements.New techniques, like Machine Learning, offer solutions to exploitmultidimensional signatures. Complementarity of these new and old approaches isstudied for the example of Higgs Boson CP-parity measurements in H totau^+tau^-, tau^pm \to nu (3pi)^pm cascade decays.

LHC Higgs CP Sensitive Observables in H to tau^+ tau^-; tau^pm to (3pi)^pm nu and Machine Learning Benefits