  Computational modeling of high entropy alloys (HEA) is challenging given the
scalability issues of Density functional theory (DFT) and the non-availability
of Interatomic potentials (IP) for molecular dynamics simulations (MD). This
work presents a computationally efficient IP for modeling complex elemental
interactions present in HEAs. The proposed random features-based IP can
accurately model melting behaviour along with various process-related defects.
The disordering of atoms during the melting process was simulated. Predicted
atomic forces are within 0.08 eV/$\unicode{xC5}$ of corresponding DFT forces.
MD simulations predictions of mechanical and thermal properties are within
7$\%$ of the DFT values. High-temperature self-diffusion in the alloy system
was investigated using the IP. A novel sparse model is also proposed which
reduces the computational cost by 94$\%$ without compromising on the force
prediction accuracy.
