The transfer of policies from simulation to physical hardware, a process known as Sim2Real, represents one of the most significant and persistent challenges in modern robotics. While simulation offers a safe, scalable, and parallelizable environment for reinforcement learning, the utility of this approach is fundamentally limited by the "reality gap"—the discrepancy between the dynamics of the simulated world and those of the real world. A policy optimized in a flawed simulation will inherit