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Abstract Slow light waveguides in photonic crystals are engineered using a conventional method or a deep learning (DL) method, which is data-intensive and suffers from data inconsistency, and both methods result in overlong computation time with low efficiency. In this paper, we overcome these problems by inversely optimizing the dispersion band of a photonic moiré lattice waveguide using automatic differentiation (AD).
Abstract We proposed an effective approach to enlarge the slow light bandwidth and normalized-delay-bandwidth product in an optimized moiré lattice-based photonic crystal waveguide that exhibits intrinsic mid-band characteristics. A flatband corresponding to a nearly constant group index of 34 over a wide bandwidth of 82 nm centered at 1550 nm with near-zero group velocity dispersion was achieved.
Abstract We analyze and optimize the performance of unconventional negative permeability (μ) metamaterial and demonstrate its ability to focus and restore the decaying Fourier harmonics (FH) in microwave regime operating frequencies.
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