Tingzhao Fu on Muck Rack

Tingzhao Fu

As seen in: Nature, Wiley Online Library, Optica
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Articles

Photonic Mixture-of-Experts for scalable multi-task on-chip optical neural networks

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By Wencan Liu, Zhenghang Zhang, Peng Meng Chan, Run Sun, Yutong He, Yuhao Wang, Caihua Zhang, Sigang Yang, Tingzhao Fu, Yuyao Huang, Chaoran Huang, Hongwei Chen
| Nature Verified
Abstract Photonic computing offers an energy-efficient, high-bandwidth platform for artificial intelligence (AI) but currently faces scalability bottlenecks stemming from depth-dependent designs, linear optical structures, and intrinsic optical losses, along with high hardware and reconfiguration costs for multi-task processing. Here, we present a scaling paradigm that circumvents these limitations by expanding network width rather than depth, leveraging the intrinsic parallelism of photonics.
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Diffraction‐Driven Parallel Convolution Processing with Integrated Photonics

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By Yuyao Huang, Wencan Liu, Run Sun, Tingzhao Fu
| Wiley Online Library Verified
Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Broadband polarization-independent infrared photon upconversion within nanophotonic lithium niobate waveguides by higher-order-mode engineering

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By Shilong Jin, Tingzhao Fu, Zhihong Zhu, Yiheng Wu
| Optica Verified
A broadband polarization-independent infrared photon upconversion scheme based on nanophotonic waveguides on the lithium niobate on insulator (LNOI) platform is proposed. With the introduction of higher-order-mode dispersion engineering, polarization-independent and broadband photon upconversion with a maximum bandwidth of nearly 46 nm is achieved in this device.
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