photonic computation for AI | ALIGN lab | Advanced Laboratory of Integrated & Guided Nanophotonics

introduction

The exponential growth of artificial intelligence and deep learning models has pushed conventional electronic hardware to its physical limits, particularly regarding energy dissipation and interconnected communication bottlenecks. Optical computing emerges as a promising paradigm to overcome these barriers, offering ultra-high bandwidth, sub-nanosecond latencies, and minimal power consumption by processing information using photons instead of electrons. By mapping complex mathematical operations directly onto light propagation and interference, photonics enables the acceleration of specialized computational workloads at the speed of light.

This research direction focuses on exploiting the unique physical properties of light to build next-generation computing hardware. We investigate novel architectures and device concepts that can seamlessly interface with existing machine learning frameworks, shifting the heavy computational burden from power-hungry digital electronics to efficient analog optical processors.

significance & applications

Augmenting or replacing traditional digital processors with photonic hardware can fundamentally transform data-heavy computing environments. The potential applications span large-scale AI data centers, autonomous systems requiring real-time edge intelligence, and high-frequency signal processing, where reducing latency and energy consumption per operation is paramount for sustainable technological scaling.

research focus

in-memory optical computing: designing non-von-Neumann computing architectures that integrate optical storage and processing elements to eliminate data movement bottlenecks. (e.g., (Wu* et al., 2024; Wu* et al., 2025))
activation and operator devices: developing non-linear optical components and dedicated hardware units to execute crucial activation functions and complex mathematical operations entirely in the optical domain.
photonic twins through emulation: implementing hardware-based photonic emulation systems to mirror and accelerate complex physical or computational processes with high fidelity. (e.g., (Wu† et al., 2022; Wu* et al., 2024; Wu* et al., 2025))

Photonic-assisted logic computations and emulations.

We are looking forward to new talent and fresh perspectives to join our endeavor.

References

2025

Intracavity Epsilon-Near-Zero Dual-Range Frequency Switch

Jiaye Wu^*, Gang Wang, Marco Clementi, Ji Zhou, Chenxingyu Huang, Xuanyi Liu, H. Y. Fu, Qian Li, and Camille-Sophie Brès^*

ACS Photonics, Mar 2025

Featured Journal Cover Art DOI Bib HTML

Featured journal cover of March 2025 issue.
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@article{Wu2025,
  title = {Intracavity Epsilon-Near-Zero Dual-Range Frequency Switch},
  author = {Wu, Jiaye and Wang, Gang and Clementi, Marco and Zhou, Ji and Huang, Chenxingyu and Liu, Xuanyi and Fu, H. Y. and Li, Qian and Br{\`e}s, Camille-Sophie},
  year = {2025},
  month = mar,
  journal = {ACS Photonics},
  volume = {12},
  number = {3},
  pages = {1276--1283},
  issn = {2330-4022},
  doi = {10.1021/acsphotonics.4c01322},
  lccn = {1},
}

2024

Versatile and Efficient Dual-Range Frequency Shifts by Intracavity Epsilon-Near-Zero Nanolayers

Jiaye Wu^*, Gang Wang, Marco Clementi, Ji Zhou, Chenxingyu Huang, Xuanyi Liu, Hongyan Fu, Qian Li, and Camille-Sophie Brès^*

In IEEE Photonics Conference (IPC), Nov 2024

DOI Bib HTML

@inproceedings{Wu2024c,
  title = {{Versatile and Efficient Dual-Range Frequency Shifts by Intracavity Epsilon-Near-Zero Nanolayers}},
  booktitle = {{IEEE Photonics Conference (IPC)}},
  author = {Wu, Jiaye and Wang, Gang and Clementi, Marco and Zhou, Ji and Huang, Chenxingyu and Liu, Xuanyi and Fu, Hongyan and Li, Qian and Br{\`e}s, Camille-Sophie},
  year = {2024},
  month = nov,
  pages = {1--2},
  publisher = {IEEE},
  address = {Rome, Italy},
  doi = {10.1109/IPC60965.2024.10799870},
  urldate = {2024-12-12},
  isbn = {979-8-3503-6195-7},
}

2022

Observation of SQUID-Like Behavior in Fiber Laser with Intra-Cavity Epsilon-Near-Zero Effect

Jiaye Wu^†, Xuanyi Liu^†, Boris A. Malomed, Kuan-Chang Chang, Minghe Zhao, Kang Qi, Yanhua Sha, Ze Tao Xie, Marco Clementi, Camille-Sophie Brès, Shengdong Zhang, Hongyan Fu^*, and Qian Li^*

Laser & Photonics Reviews, Dec 2022

DOI arXiv Bib HTML

@article{Wu2022,
  title = {{Observation of SQUID-Like Behavior in Fiber Laser with Intra-Cavity Epsilon-Near-Zero Effect}},
  author = {Wu, Jiaye and Liu, Xuanyi and Malomed, Boris A. and Chang, Kuan-Chang and Zhao, Minghe and Qi, Kang and Sha, Yanhua and Xie, Ze Tao and Clementi, Marco and Br{\`e}s, Camille-Sophie and Zhang, Shengdong and Fu, Hongyan and Li, Qian},
  year = {2022},
  month = dec,
  journal = {Laser \& Photonics Reviews},
  volume = {16},
  number = {12},
  pages = {2200487},
  issn = {1863-8880},
  doi = {10.1002/lpor.202200487},
  lccn = {1},
}