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For the last several decades, there has been tremendous interest in search for Supersymmetry (SUSY) in the area of high energy physics. At Large Hadron Collider (LHC), there have been continuous searches for SUSY for prompt and non-prompt, for particle R-parity conserving and R-parity violating generation and decays. The limits obtained from these experiments and analyses for detection of the signatures of supersymmetric particles (LSP), revealed greater possibilities of such experiments in the collider. However, these signatures are usually derived under the assumption of bit optimistic conditions of the decaying process of sparticles to the final states. Moreover, SUSY might have been in a disguised state at lower mass-scales as a result of difficult and challenging mass spectra and mixed modes of decays. In this investigation, a novel method of 3-dimensional (3D) Visibility-Graph Analysis is proposed. This is an extension of Visibility Graph analysis of data series to perform the scaling analysis for 3D space. The experimental data spaces analyzed are made up of the component-space (in the X,Y and Z coordinates) of transverse momentum (pT) values taken out from 4-momenta of the signatures of the final state of the pair of mega-jets extracted from the multiJet primary pp collision data from Run B of 2010 at 7 TeV which was used for the search of SUSY using razor filter. The symmetry scaling and the inherent scaling behavior, scale-freeness of multi-particle production process is studied in terms of 3D Power-of-Scale-freeness-of-Visibility-Graph (3D-PSVG) extracted from the 3D Visibility Graphs constructed out of the experimental data spaces. The signature of SUSY may be identified by analyzing the scaling behavior and long-range correlation inherent in the 3D space made up of signatures of final state of multi-particles produced in the pp collision at 7 TeV, for the analysis of SUSY, which the conventional method of analyzing the spectrum of invariant mass or pT may miss.

Searching for Supersymmetry at LHC Using the Complex-Network-Based Method of the Three-Dimensional Visibility-Graph