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Leveraging Low Index Contrast to Reduce the Polarization Anisotropy in One-Dimensional Photonic Crystals

Published 17 Jul 2025 in physics.optics | (2507.13193v1)

Abstract: One-dimensional photonic crystals (1DPCs) are widely used platforms for guiding, filtering, and enhancing light at the nanoscale. Traditionally, designs have favored high refractive index contrast to maximize the photonic band gap (PBG) size. Here, we demonstrate that low-index contrast systems offer a powerful and underexplored route to achieving improved optical functionalities. In particular, we show that low index contrast enables more closely aligned PBGs for transverse electric (TE) and transverse magnetic (TM) polarizations, allowing for broadband superposition of TE and TM Bloch Surface Waves (BSWs). As a demonstration of this functionality, we use this approach to design 1DPCs capable of generating planar superchiral fields for enhanced circular dichroism spectroscopy. To realize such structures, we use an automated design framework based on multi-objective genetic optimization. By comparing optimized designs in both high and low index contrast regimes, we find that low index contrast systems yield significantly greater overlap between the TE and TM BSW dispersion relations and exhibit a pronounced reduction in optical anisotropy - both of which contribute to enhanced optical chirality across the operational bandwidth. Furthermore, simulations reveal that these low index contrast structures offer improved robustness to fabrication tolerances and support a wider dynamic range of chiral analyte concentrations. In addition to their optical performance advantages, low-index contrast systems are naturally compatible with polymeric materials, which offer benefits such as low cost, sustainability, and mechanical flexibility. While this work focuses on mode alignment and its consequences for surface wave behavior, the underlying principles have broader implications for polarization-independent photonic technologies, including optical sensing, computing, and spectral filtering.

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