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Nan Chi

Publications and source records attributed to Nan Chi.

7 recordsLinked to original sources
arXiv2026

Reinforcement Learning-Enabled Agent for Transmitter Optimization in Digital-Analog Radio-over-Fiber Fronthaul

Digital-analog radio-over-fiber (DA-RoF) has emerged as a promising fronthaul solution that combines the high spectral efficiency of analog transmission with the robustness of digital transmission. However, the performance of DA-RoF critically depends on several tightly coupled parameters, including the rounding factor (RF), scaling factor (SF), geometric shaping (GS) factor, and pre-equalization taps coefficients, which jointly affect quantization noise, nonlinear distortion, and bandwidth-induced inter-symbol interference (ISI). Conventional grid search-based optimization is computationally prohibitive and impractical for optical communication. In this work, we propose a reinforcement-learning (RL)-enabled DA-RoF fronthaul agent architecture, capable of autonomously learning optimal transmitter parameters from end-to-end signal-to-noise ratio (SNR) feedback without a differentiable channel model. Experimental results demonstrate that the trained agent steadily improves SNR through sequential decision making and outperforms baseline, achieving ~2.7-dB SNR improvement for 1- to 4-order DA-RoF transmission, reaching final SNR of 35.8 dB, 42.9 dB, 53.8 dB, and 63.2 dB and supporting 1024-, 4096-, 16384-, 65536-quadrature amplitude modulation (QAM) format, respectively. These results validate that the proposed RL-enabled framework provides online, scalable, and hardware-efficient parameter optimization for DA-RoF fronthaul systems, paving the way toward high-order modulation format and intelligent next-generation radio access networks.

physics.optics↗
arXiv2026

Fully multiplexed photonic tensor computing

Tensor operations dominate modern computational workloads, yet their further acceleration demands hardware platforms with greater parallelism. Although photonic computing provides a compelling route for parallel processing, fully exploiting all native multiplexing dimensions of optical fields is impeded by the challenges in routing and programming light in all dimensions simultaneously. Here we introduce FieldCore, a fully multiplexed photonic tensor core that jointly harnesses wavelength, radio-frequency, guided-mode, time and space dimensions, thereby enabling parallelism to scale multiplicatively within a single optical field. Enabled by inverse-designed silicon photonics, FieldCore preserves a uniform programmed computation across all multiplexed channels in parallel. Experimentally, we validate and benchmark its performance from ultra-high-baudrate arithmetic operations to high-fidelity image convolution and parallel handwritten-digit recognition. We further use FieldCore to unlock applications that naturally require high-dimensional data processing, such as high-dimensional hyperspectral classification and massively parallel mechanical fault diagnosis. Our FieldCore supports an estimated aggregate compute throughput of 69.12 tera operations per second (TOPS) and accommodates up to 1,800 parallel input streams within a single core, establishing a scalable paradigm for fully multiplexed photonic tensor computing and AI inference.

physics.optics↗
arXiv2024

Seamless Optical Cloud Computing across Edge-Metro Network for Generative AI

The rapid advancement of generative artificial intelligence (AI) in recent years has profoundly reshaped modern lifestyles, necessitating a revolutionary architecture to support the growing demands for computational power. Cloud computing has become the driving force behind this transformation. However, it consumes significant power and faces computation security risks due to the reliance on extensive data centers and servers in the cloud. Reducing power consumption while enhancing computational scale remains persistent challenges in cloud computing. Here, we propose and experimentally demonstrate an optical cloud computing system that can be seamlessly deployed across edge-metro network. By modulating inputs and models into light, a wide range of edge nodes can directly access the optical computing center via the edge-metro network. The experimental validations show an energy efficiency of 118.6 mW/TOPs (tera operations per second), reducing energy consumption by two orders of magnitude compared to traditional electronic-based cloud computing solutions. Furthermore, it is experimentally validated that this architecture can perform various complex generative AI models through parallel computing to achieve image generation tasks.

cs.DC↗
arXiv2024

D-band MUTC Photodiode Module for Ultra-Wideband 160 Gbps Photonics-Assisted Fiber-THz Integrated Communication System

Current wireless communication systems are increasingly constrained by insufficient bandwidth and limited power output, impeding the achievement of ultra-high-speed data transmission. The terahertz (THz) range offers greater bandwidth, but it also imposes higher requirements on broadband and high-power devices. In this work, we present a modified uni-traveling-carrier photodiode (MUTC-PD) module with WR-6 waveguide output for photonics-assisted fiber-THz integrated wireless communications. Through the optimization of the epitaxial structure and high-impedance coplanar waveguide (CPW), the fabricated 6-um-diameter MUTC-PD achieves a high output power of -0.96 dBm at 150 GHz and ultra-flat frequency response at D-band. The MUTC-PD is subsequently packaged into a compact WR-6 module, incorporating planar-circuit-based RF-choke, DC-block and probe. The packaged PD module demonstrates high saturation power and flat frequency responses with minimal power roll-off of only 2 dB over 110-170 GHz. By incorporating the PD module into a fiber-THz integrated communication system, high data rates of up to 160 Gbps with 16 quadrature amplitude modulation (QAM) and a maximum symbol transmission rate of 60 Gbaud with QPSK modulation are successfully secured. The demonstration verifies the potential of the PD module for ultra-broadband and ultra-high-speed THz communications, setting a foundation for future research in high-speed data transmission.

physics.optics↗
arXiv2024

Edge-guided inverse design of digital metamaterial-based mode multiplexers for high-capacity multi-dimensional interconnect

The escalating demands of compute-intensive applications urgently necessitate the adoption of optical interconnect technologies to overcome bottlenecks in scaling computing systems. This requires fully exploiting the inherent parallelism of light across scalable dimensions for data loading. Here we experimentally demonstrate a synergy of wavelength- and mode- multiplexing combined with high-order modulation formats to achieve multi-tens-of-terabits-per-second optical interconnects using foundry-compatible silicon photonic circuits. Implementing an edge-guided analog-and-digital optimization method that integrates high efficiency with fabrication robustness, we achieve the inverse design of mode multiplexers based on digital metamaterial waveguides. Furthermore, we employ a packaged five-mode multiplexing chip, achieving a single-wavelength interconnect capacity of 1.62 Tbit s-1 and a record-setting multi-dimensional interconnect capacity of 38.2 Tbit s-1 across 5 modes and 88 wavelength channels, with high-order formats up to 8-ary pulse-amplitude-modulation (PAM). This study highlights the transformative potential of optical interconnect technologies to surmount the constraints of electronic links, thus setting the stage for next-generation datacenter and optical compute interconnects.

physics.optics↗
arXiv2021

Beyond 300Gbps Silicon Microring Modulator with AI Acceleration

Silicon microring modulator (Si-MRM) has become one of the most promising compact modulators to meet the increasing capacity requirements of the next generation optical interconnection. The limited electro-optical (E-O) bandwidth, low modulation efficiency, and inherent modulation nonlinearity are the major factors that limit the Si-MRM modulation speed. To address these issues, we comprehensively optimize the Si-MRM from the device to the modulation and the signal processing. Large modulation bandwidth over 67GHz is achieved in our newly fabricated Si-MRM. Additionally, the laser wavelength and bias voltage of Si-MRM are optimized to significantly improve the modulation performance. Finally, we comprehensively study the theoretical model of modulation nonlinearity in Si-MRM, especially transient nonlinearity. A bidirectional gate recurrent unit (Bi-GRU) neural network with minor modification is applied to compensate for the nonlinear impairments. With all these efforts, we experimentally demonstrate a 302 Gbps Si-MRM-based O-band optical interconnection and achieve 300 Gbps transmission over a 1-km standard single-mode fiber using the discrete multitone modulation format with bit and power loading (BPL-DMT).

physics.app-ph↗