Deep learning prediction of novel hollow core photonic crystal fiber with tuned As2S3 − LiNbO3 ring for multimode applications

Abstract

Multimode capability in photonic crystal fiber (PCF) is an important feature in fiber development. This study presents an innovative Dual Ring Hollow core PCF (DRH-PCF), designed to support a large number of multimode operations with minimal loss and flat dispersion optimized in the wavelength range of 1.26 µm to 1.66 µm. The DRH-PCF structure comprises a high-purity silica matrix, featuring a unique configuration that includes a hollow core and high indexed Lithium niobate (LiNbO3)-Arsenic trisulfide (As2S3) dual rings of thickness 0.6 µm. This arrangement is complemented by a pattern of strategically placed air holes encircling the fiber. Our PCF is engineered to support an impressive 200 and more orbital angular momentum modes, with low confinement loss (∼10−5 dB/m) and near-flat dispersion (∼3 ps/mm/km) and very large power fraction (∼0.99), while maintaining high mode purity of >95 %. Furthermore, the fiber exhibits a near-flat dispersion profile over a wide spectral range, with a measured dispersion of ∼6 ps/(nm·km) around the operational wavelength. Stability due to fiber bend is also investigated for extreme bend tolerance (Bend radii RB=1cm to 80 cm). Deep Learning prediction is used to train and predict the performance of the fiber and obtained remarkably close results (within 5 %). This combination of features makes our PCF an excellent candidate for diverse applications in high-capacity optical communication systems, sensing technologies, and nonlinear optics.