A Power‐Efficient Monte Carlo Framework for Nonlinear Light–Matter Interactions: In Silico Modeling of Spontaneous and Stimulated Raman Scattering in Turbid Media

We present a power‐efficient Monte Carlo simulation framework for modeling nonlinear light–matter interactions, with a particular focus on spontaneous and stimulated Raman scattering (SRS) in turbid biological media. By leveraging Apple's unified memory architecture and implementing a highly parallelized photon transport kernel using the Metal Shading Language, our method achieves substantial gains in computational efficiency without compromising accuracy. The algorithm incorporates a probabilistic treatment of nonlinear scattering events and introduces shared photon‐state management to simulate complex interactions, including second‐order processes such as SRS. Validation against established benchmarks demonstrates excellent agreement across spatial and temporal domains. Our results reveal a nontrivial dependence of SRS efficiency on the detection and turbid media parameters, highlighting the algorithm's capability to resolve subtle photon–photon interactions. The proposed framework offers a scalable and energy‐efficient platform for advanced optical modeling, with potential applications in biomedical diagnostics, remote sensing, and photonics research.