True-time delay and mode-matching in Archimedean spiral silicon photonic waveguides

Abstract We report a comprehensive analysis and design optimization of true-time delay (TTD) photonic waveguides using compact Archimedean spiral geometries, with a focus on low-loss silicon nitride (Si 3 N 4 ) and silicon-on-insulator (SOI) platforms. Using a combination of finite element and finite-difference time-domain simulations at 1550 nm, we evaluated the propagation characteristics, mode-matching behavior, and bending losses of various waveguide designs. Our results demonstrate that Si 3 N 4 rectangular waveguides exhibit superior performance for long optical paths, achieving minimal radiation and scattering losses, whereas SOI is more suitable for compact integration. We further investigated curvature-engineered bends (Euler, Bézier, and circular) and identified Quartic Bézier bends as optimal for tight-radius, low-loss guiding. By minimizing crosstalk through tailored waveguide gaps and carefully engineered S-bend transitions, we present a scalable low-loss TTD architecture. These findings offer critical insights for integrating ultralow-loss, material-efficient delay lines into photonic circuits for applications in signal processing, LiDAR, phased array antennas, and neuromorphic computing.

Authors

Institutions

Publication Details

Journal
Engineering Research Express
Published
2025-09-05
DOI
https://doi.org/10.1088/2631-8695/ae0413
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

True-time delay and mode-matching in Archimedean spiral silicon photonic waveguides

Alina Karabchevsky, Ahmad Murad
Engineering Research Express
Neural Networks and Reservoir Computing
article

True-time delay and mode-matching in Archimedean spiral silicon photonic waveguides

Alina Karabchevsky, Ahmad Murad
article en

Abstract

Abstract We report a comprehensive analysis and design optimization of true-time delay (TTD) photonic waveguides using compact Archimedean spiral geometries, with a focus on low-loss silicon nitride (Si 3 N 4 ) and silicon-on-insulator (SOI) platforms. Using a combination of finite element and finite-difference time-domain simulations at 1550 nm, we evaluated the propagation characteristics, mode-matching behavior, and bending losses of various waveguide designs. Our results demonstrate that Si 3 N 4 rectangular waveguides exhibit superior performance for long optical paths, achieving minimal radiation and scattering losses, whereas SOI is more suitable for compact integration. We further investigated curvature-engineered bends (Euler, Bézier, and circular) and identified Quartic Bézier bends as optimal for tight-radius, low-loss guiding. By minimizing crosstalk through tailored waveguide gaps and carefully engineered S-bend transitions, we present a scalable low-loss TTD architecture. These findings offer critical insights for integrating ultralow-loss, material-efficient delay lines into photonic circuits for applications in signal processing, LiDAR, phased array antennas, and neuromorphic computing.

Engineering Research ExpressVol. 7(3)
Ben-Gurion University of the Negev (IL)
Openalex Percentile: Top 88%
Neural Networks and Reservoir Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.