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As high-performance computing and artificial intelligence become increasingly intertwined, the need for three-dimensional electromagnetic numerical simulation has surged across various domains, including radar systems, photonic crystal research, and geophysical exploration. The Crank-Nicolson Finite-Difference Time-Domain (CN-FDTD) method stands out as a pivotal technique in electromagnetic simulation, valued for its unconditional stability and energy-conserving characteristics. This makes it a preferred choice for large-scale, extended-duration simulations. Nevertheless, the method's reliance on solving a vast sparse linear system, composed of double curl operators at every time step, leads to substantial computational expenses. This, in turn, restricts its practical engineering applications.
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