Constraining Different SUSY Models in the Light of LHC Experiments

Choudhury, Arghya (2013) Constraining Different SUSY Models in the Light of LHC Experiments. PhD thesis, Indian Institute of Science Education and Research Kolkata.

PDF (PhD thesis of Arghya Choudhury) Thesis_Arghya_Choudhury_Final.pdf - Submitted Version Restricted to Repository staff only Download (5MB)

Abstract

Despite the great success in explaining a wide variety of experiments, the Standard Model (SM) has far too much shortcomings to be the final story. The most well known theoretical objection to the SM is the hierarchy problem. SM also can not explain the naturalness problem and why neutrinos are so light compared to the charged fermions. The SM is not the theory of everything as gravity is not included in it. There is no particle in the SM that is a viable candidate for the observed dark matter (DM) in the universe. Supersymmetry formalism with details and references have been discussed. The present bounds on the sparticle masses from LHC 7 and 8 TeV runs obtained by ATLAS and CMS are summarised in this work.As dark matter is one of the main feature of my thesis, a brief review on DM has been included in this thesis. We have identified the parameter spaces allowed by the relic density data and explored the impact of the LHC constraints in various models like the Light Gaugino and R-slepton (LGRS) model, the Light Gaugino and L-Slepton (LGLS) model, the Light Gaugino and Heavy Slepton (LGHS) model etc. We found that LSP annihilation via the light higgs scalar resonance or via t-channel slepton annihilation (bulk annihilation) as well as neutralino coannihilations with various nearly degenerate NLSPs (like slepton, sneutrino, chargino etc.) can produce correct DM relic density in several models considered in without any conflict with the LHC direct searches. We have also studied the relaxation of the gluino mass limit in the light slepton scenario, assuming heavy squarks. The searches must be extended to 13/14 TeV experiments with improved search strategies in the context of more general models.

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