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Can I read Higgs Boson Decays Into a Pair of Bottom Quarks : Observation with the ATLAS Detector and Machine Learning Applications on EtoBox?

Higgs Boson Decays Into a Pair of Bottom Quarks : Observation with the ATLAS Detector and Machine Learning Applications by Cecilia Tosciri is a nonfiction available to read on EtoBox.

What is Higgs Boson Decays Into a Pair of Bottom Quarks : Observation with the ATLAS Detector and Machine Learning Applications about?

The discovery in 2012 of the Higgs boson at the Large Hadron Collider (LHC) represents a milestone for the Standard Model (SM) of particle physics. Most of the SM Higgs production and decay rates have been measured at the LHC with increased precision. However, despite its experimental success, the SM is known to be only an effective manifestation of a more fundamental description of nature. The scientific research at the LHC is strongly focused on extending the SM by searching, directly or indirectly, for indications of New Physics. The extensive physics program requires increasingly advanced computational and algorithmic techniques. In the last decades, Machine Learning (ML) methods have made a prominent appearance in the field of particle physics, and promise to address many challenges faced by the LHC. This thesis presents the analysis that led to the observation of the SM Higgs boson decay into pairs of bottom quarks. The analysis exploits the production of a Higgs boson associated with a vector boson whose signatures enable efficient triggering and powerful background reduction. The main strategy to maximise the signal sensitivity is based on a multivariate approach. The analy

Who reads Higgs Boson Decays Into a Pair of Bottom Quarks : Observation with the ATLAS Detector and Machine Learning Applications?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Cecilia Tosciri
Publisher
Springer International Publishing : Imprint: Springer
Published
2021
Language
EN
ISBN
9783030879372
Category
nonfiction
Subjects
Mathematics, Science, Computer Science

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