arXiv subjects

Xiansong Meng

Publications and source records attributed to Xiansong Meng.

3 recordsLinked to original sources

arXiv2026

Ion-Implanted Silicon Nanoregions Enable Ultra-Low-Loss Trimming of Cladded Photonic Integrated Circuits

Photonic integrated circuits (PICs) have emerged as a key platform for information processing, including optical communication and computing. As PIC complexity increases, fabrication-induced response deviations accumulate, making post-fabrication trimming critical for unlocking their full potential. Here, we demonstrate that silicon ion implantation enables scalable, ultra-low-loss trimming of cladded PICs by locally forming a high-index silicon-rich region. Structural characterization confirms that the silicon-implanted nanoregion is confined to the cladding without observable damage to the underlying waveguide. The implantation-induced excess loss is below 0.001 dB per {\pi} phase shift, while the optical response remains stable over a four-month observation period. Automated trimming is demonstrated on a photonic crossbar array, reducing the average channel output variation from 78.5% to 5.9%. These results establish a practical route towards automated, ultra-low-loss post-fabrication trimming for large-scale cladded PICs.

physics.optics↗

arXiv2025

1000-Channel Integrated Optical Phased Array with 180° Field of View, High Resolution and High Scalability

Optical phased array (OPA) is a promising technology for compact, solid-state beam steering, with applications ranging from free-space optical communication to LiDAR. However, simultaneously achieving a large field of view (FOV), high resolution, and low side-lobe level (SLL) remains a major challenge. Traditional OPAs face inherent limitations: they exhibit grating lobes when emitter spacing exceeds half the operating wavelength, while at half-wavelength spacing, significant crosstalk issues persist. Previously, we demonstrated a small-scale OPA that harnesses near-field interference and beamforming via a trapezoidal slab grating and a half-wavelength-pitch waveguide array to achieve a 180° FOV. However, its resolution was limited by the small channel count. In this work, we present a 1000-channel OPA that scales this architecture while addressing key challenges in waveguide crosstalk and control complexity. By optimizing waveguide routing, we minimize inter-channel coupling in the dense waveguide array. Additionally, we propose and demonstrate a passive matrix control scheme using 20 row and 50 column pulse-width modulation (PWM) signals to arbitrarily control 1000 thermo-optic phase shifters, significantly simplifying the electronic control and packaging. Our OPA achieves grating-lobe-free beam steering across a full 180° FOV, with a high resolution of 0.07° * 0.17° and a minimum SLL of -18.7 dB at 0°. This large-scale, cost-effective chip-based OPA paves the way for next-generation high-resolution, wide-angle beam steering systems.

physics.optics↗

arXiv2024

Digital-analog hybrid matrix multiplication processor for optical neural networks

The computational demands of modern AI have spurred interest in optical neural networks (ONNs) which offer the potential benefits of increased speed and lower power consumption. However, current ONNs face various challenges,most significantly a limited calculation precision (typically around 4 bits) and the requirement for high-resolution signal format converters (digital-to-analogue conversions (DACs) and analogue-to-digital conversions (ADCs)). These challenges are inherent to their analog computing nature and pose significant obstacles in practical implementation. Here, we propose a digital-analog hybrid optical computing architecture for ONNs, which utilizes digital optical inputs in the form of binary words. By introducing the logic levels and decisions based on thresholding, the calculation precision can be significantly enhanced. The DACs for input data can be removed and the resolution of the ADCs can be greatly reduced. This can increase the operating speed at a high calculation precision and facilitate the compatibility with microelectronics. To validate our approach, we have fabricated a proof-of-concept photonic chip and built up a hybrid optical processor (HOP) system for neural network applications. We have demonstrated an unprecedented 16-bit calculation precision for high-definition image processing, with a pixel error rate (PER) as low as $1.8\times10^{-3}$ at an signal-to-noise ratio (SNR) of 18.2 dB. We have also implemented a convolutional neural network for handwritten digit recognition that shows the same accuracy as the one achieved by a desktop computer. The concept of the digital-analog hybrid optical computing architecture offers a methodology that could potentially be applied to various ONN implementations and may intrigue new research into efficient and accurate domain-specific optical computing architectures for neural networks.

cs.NE↗