Ultrafast Electro-Optic Spiking Membrane III-V Lasers on Silicon Utilizing Integrated Optical Feedback

被引:1
|
作者
Diamantopoulos, Nikolaos-Panteleimon [1 ]
Fujii, Takuro [1 ]
Yamaoka, Suguru [1 ,2 ]
Nishi, Hidetaka [1 ]
Matsuo, Shinji [1 ]
机构
[1] NTT Corp, NTT Device Technol Labs, Atsugi, Kanagawa 2430198, Japan
[2] NTT Corp, NTT Access Network Serv Syst Labs, Yokosuka 2390847, Japan
关键词
Optical feedback; Laser feedback; Laser modes; Photonics; Optical pulses; Vertical cavity surface emitting lasers; Power lasers; Heterogeneous integration; membrane lasers; neuromorphic photonics; spiking lasers; spiking neural networks; EXCITABILITY; NETWORKS; NEURONS;
D O I
10.1109/JLT.2024.3428532
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper summarizes various experimental results on the characterization of the novel spiking membrane lasers on SiO2/Si and their spiking dynamics. The ultra-thin (<350-nm-thick) membrane III-V on SiO2/Si structure results in a very high optical confinement factor which is suitable for both increasing processing speeds and minimizing power consumptions. Moreover, for spiking generation we rely on bi-modal dynamics based on integrated optical feedback, which is a more efficient approach than other methods that rely on (slower) carrier-photon dynamics. Based on this, we report the first (to the best of our knowledge) bi-modal spiking laser capable of producing spikes via electrical inputs, suitable for various multiplexing approaches. Aiming to go beyond the state-of-the-art, the list of achievements in the present work includes demonstrated novel electro-optic excitability using up to 60 GBaud electrical input pulses, spiking rates of more than 12.5 GHz, spikes pulse widths of similar to 10 ps, static operating energies in the order of similar to 1 pJ/spike, and threshold energies of few similar to 100 fJ/spike. Noticeable spiking effect stability and reproducibility are also reported. We believe that these results pave the way towards future multi-neuron membrane photonic spiking neural networks and neuromorphic photonic systems-on-chip, offering enhanced processing speeds, scalability, and energy-efficiency for AI applications.
引用
收藏
页码:7776 / 7784
页数:9
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