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This work presents a hybrid computing technique for modeling the differential elastic cross section of both proton–proton “pp” and proton–antiproton “pp(bar)” collisions from high to ultra-high energy regions (from 13.9 GeV to 14 TeV) as a function of the center-of-mass energy “s” squared and four momentum transfer squared “t”. We proposed a genetic algorithm (GA) and support vector regression (SVR) hybrid techniques to calculate and predict the “differential elastic cross section” of both “pp” and “pp(bar)”. Our proposed GA-SVR hybrid model shows a good match to the available experimental data, as well as predicting the latest and future “TOTEM” experiments for differential elastic cross sections that are not utilized in the training phase. An extrapolation of the differential cross section to |t| →0 gives the total cross section through the optical theorem. The model calculations and predictions for “pp” and “pp(bar)” total cross-sections over a wide collision energy ranging from ISR to LHC are given. All the results for the total cross-sections matched well with the last and the more recent measurements ( √ s= 7 TeV and 8 TeV), as well as the results of other models for the future “TOTEM” measurements at ( √ s = 10 TeV and 14 TeV).

Proton--proton and proton--antiproton differential elastic cross sections modeling at high and ultra-high energies using a hybrid computing paradigm