Machine learning techniques in the search for double Higgs production at the LHC


  • Call:

    IDPASC Portugal - PHD Programme 2016

  • Academic Year:

    2016 / 2017

  • Domain:

    Experimental Particle Physics

  • Supervisor:

    Michele Gallinaro

  • Co-Supervisor:

    Joao Varela

  • Institution:

    Instituto Superior Técnico

  • Host Institution:

    Laboratório de Instrumentação e Física Experimental de Partículas

  • Abstract:

    The subject of this thesis is the search for new physics processes in double Higgs production, decaying into taus and b-jets, at the Large Hadron Collider (LHC). The thesis is placed in the context of the Portuguese participation in the CMS experiment at the LHC, and it is linked to the Beyond the Standard Model (BSM) searches in the more general context of the searches for New Physics processes at the LHC. In the course of the last forty years the SM has received increasing and consistent verification by precise experimental tests of its predictions, culminating in 2012 with the discovery of a new particle, which appears to be called “the” Higgs boson. There are, however, compelling reasons to believe the SM is not complete. In particular, the LIP/CMS group is engaged in the study of SM and BSM processes to fully exploit the opportunities of the unparalleled energy of the LHC collisions. Searches for BSM processes have been carried out in the 2010-2012 data taking periods at center-of-mass-energies of 7 and 8 TeV. The higher proton-proton collision energy at 13 TeV started in 2015 is foreseen to continue for a few more years, and it will offer excellent opportunities for major discoveries in this domain during 2016 and beyond. The work plan includes the study of the double Higgs production, each subsequently decaying to pairs of taus and b-jets. Advanced multi-variate analysis (MVA) techniques developed in the context of the EU project AMVA4NewPhysics will be used in the data analysis.