Laser-driven inertial confinement fusion represents a key pathway toward controlled nuclear fusion. Radiation hydrodynamic simulations play an important role in the design and assessment of ICF experiments. Laser plasma instabilities such as stimulated Raman scattering reduce the energy coupling efficiency and generate hot electrons that preheat the target, thereby degrading implosion performance. SRS is a microscopic process that poses a challenge for direct coupling into macroscopic radiation hydrodynamic codes, compromising the physical accuracy of simulations. In this work, we scanned the parameter space of SRS using a series of particle-in-cell   simulations. Machine learning methods were then employed to extract scaling laws for the hot electron fraction generated by SRS and the associated energy attenuation. These relations were subsequently incorporated into the radiation hydrodynamic code IceFire2D, enabling a preliminary exploration of the coupling between microscopic SRS and macroscopic radiation hydrodynamic simulations.

inertial confinement fusion,laser plasma instability,Stimulated Raman scattering (SRS),radiation hydrodynamic code,Particle-in-cell (PIC)