Ultrafast Reconfigurable Topological Photonic Processing Accelerator
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arXiv
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| Autori principali: | , , , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914138892009472 |
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| author | Zhou, Wenfeng Wang, Xin Zhang, Xun Chen, Yuqi Sun, Min Li, Jingchi Ni, Xiong Zhu, Yahui Han, Qingqing Wang, Jungan Yang, Chen Li, Bin Qiu, Feng Su, Yikai Zhang, Yong |
| author_facet | Zhou, Wenfeng Wang, Xin Zhang, Xun Chen, Yuqi Sun, Min Li, Jingchi Ni, Xiong Zhu, Yahui Han, Qingqing Wang, Jungan Yang, Chen Li, Bin Qiu, Feng Su, Yikai Zhang, Yong |
| contents | The rise of artificial intelligence has triggered exponential growth in data volume, demanding rapid and efficient processing. High-speed, energy-efficient, and parallel-scalable computing hardware is thus increasingly critical. We demonstrate a wafer-scale non-volatile topological photonic computing chip using topological modulators. Leveraging the GHz-speed electro-optic response and nonvolatility of ferroelectric lead zirconate titanate (PZT) thin films via topological photonic confinement, Our chip enables thousand-fold faster reconfiguration, zero-static-power operation, and a computational density of 266 trillion operations per second per square millimeter . This density surpasses that of silicon photonic reconfigurable computing chips by two orders of magnitude and thin-film lithium niobate platforms by four orders of magnitude. A 16-channel wavelength-space multiplexed chip delivers 1.92 TOPS throughput with 95.64% digit-recognition accuracy and 94.5% precision for solving time-varying partial differential equations. Additionally, the chip supports functional reconfiguration for high bandwidth density optical I/O. This work establishes ferroelectric topological photonics for efficient high-speed photonic tensor processing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_03432 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Ultrafast Reconfigurable Topological Photonic Processing Accelerator Zhou, Wenfeng Wang, Xin Zhang, Xun Chen, Yuqi Sun, Min Li, Jingchi Ni, Xiong Zhu, Yahui Han, Qingqing Wang, Jungan Yang, Chen Li, Bin Qiu, Feng Su, Yikai Zhang, Yong Optics Applied Physics The rise of artificial intelligence has triggered exponential growth in data volume, demanding rapid and efficient processing. High-speed, energy-efficient, and parallel-scalable computing hardware is thus increasingly critical. We demonstrate a wafer-scale non-volatile topological photonic computing chip using topological modulators. Leveraging the GHz-speed electro-optic response and nonvolatility of ferroelectric lead zirconate titanate (PZT) thin films via topological photonic confinement, Our chip enables thousand-fold faster reconfiguration, zero-static-power operation, and a computational density of 266 trillion operations per second per square millimeter . This density surpasses that of silicon photonic reconfigurable computing chips by two orders of magnitude and thin-film lithium niobate platforms by four orders of magnitude. A 16-channel wavelength-space multiplexed chip delivers 1.92 TOPS throughput with 95.64% digit-recognition accuracy and 94.5% precision for solving time-varying partial differential equations. Additionally, the chip supports functional reconfiguration for high bandwidth density optical I/O. This work establishes ferroelectric topological photonics for efficient high-speed photonic tensor processing. |
| title | Ultrafast Reconfigurable Topological Photonic Processing Accelerator |
| topic | Optics Applied Physics |
| url | https://arxiv.org/abs/2511.03432 |