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Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named AMVA4NewPhysics studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones. Many of those methods were successfully used to improve the sensitivity of data analyses performed by the ATLAS and CMS experiments at the CERN Large Hadron Collider; several others, still in the testing phase, promise to further improve the precision of measurements of fundamental physics parameters and the reach of searches for new phenomena. In this paper, the most relevant new tools, among those studied and developed, are presented along with the evaluation of their performances.
The Large Hadron Collider presents an unprecedented opportunity to probe the realm of new physics in the TeV region and shed light on some of the core unresolved issues of particle physics. These include the nature of electroweak symmetry breaking, t
Convincing and direct evidence for dark matter (DM) on galactic scales comes from the observation of the rotation curves of galaxies. At particle colliders, searches for DM involve the production of a pair of stable electrically neutral and weakly in
The high energy programme of the HERA collider ended in March 2007. During the whole HERA programme, a combined total integrated luminosity of 1 fb$^{-1}$ was collected by the H1 and ZEUS experiments. In this context, an overview of the most recent r
This paper reviews the most recent results on searches for physics beyond the Standard Model at Tevatron. Both the collider experiments: CDF and DO are performing a large variety of searches such as searches for scalar top and scalar bottom particles
This review focuses on the expected performance of the ATLAS and CMS detectors at the CERN Large Hadron Collider (LHC), together with some of the highlights of the global commissioning work done in 2008 with basically fully operational detectors. A s