Current status of the light neutralino thermal dark matter in the phenomenological MSSM

In a previous publication, we studied the parameter space of the phenomenological minimal Super- symmetric standard model with a light neutralino thermal dark matter ( M x 01 <= M h / 2) and observed that the recent results from the dark matter and collider experiments put strong constraints on this scenario. In this work, we present in detail the arguments behind the robustness of this result against scanning over the large number of parameters in phenomenological minimal Supersymmetric standard model. The Run 3 of LHC will be crucial in probing the surviving regions of the parameter space. We further investigate the impact of light staus on our parameter space and also provide benchmarks that can be interesting for Run 3 of LHC. We analyze these benchmarks at the LHC using the machine learning framework of XGBOOST. Finally, we also discuss the effect of nonstandard cosmology on the parameter space.