scholarly journals State of the Art and Perspectives on Silicon Photonic Switches

Micromachines ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 51 ◽  
Author(s):  
Xin Tu ◽  
Chaolong Song ◽  
Tianye Huang ◽  
Zhenmin Chen ◽  
Hongyan Fu

In the last decade, silicon photonic switches are increasingly believed to be potential candidates for replacing the electrical switches in the applications of telecommunication networks, data center and high-throughput computing, due to their low power consumption (Picojoules per bit), large bandwidth (Terabits per second) and high-level integration (Square millimeters per port). This review paper focuses on the state of the art and our perspectives on silicon photonic switching technologies. It starts with a review of three types of fundamental switch engines, i.e., Mach-Zehnder interferometer, micro-ring resonator and micro-electro-mechanical-system actuated waveguide coupler. The working mechanisms are introduced and the key specifications such as insertion loss, crosstalk, switching time, footprint and power consumption are evaluated. Then it is followed by the discussion on the prototype of large-scale silicon photonic fabrics, which are based on the configuration of above-mentioned switch engines. In addition, the key technologies, such as topological architecture, passive components and optoelectronic packaging, to improve the overall performance are summarized. Finally, the critical challenges that might hamper the silicon photonic switching technologies transferring from proof-of-concept in lab to commercialization are also discussed.

Author(s):  
Zhou Zhao ◽  
Ben Gao ◽  
Vincent W. Zheng ◽  
Deng Cai ◽  
Xiaofei He ◽  
...  

Link prediction is a challenging problem for complex network analysis, arising in many disciplines such as social networks and telecommunication networks. Currently, many existing approaches estimate the proximity of the link endpoints for link prediction from their feature or the local neighborhood around them, which suffer from the localized view of network connections and insufficiency of discriminative feature representation. In this paper, we consider the problem of link prediction from the viewpoint of learning discriminative path-based proximity ranking metric embedding. We propose a novel ranking metric network learning framework by jointly exploiting both node-level and path-level attentional proximity of the endpoints for link prediction. We then develop the path-based dual-level reasoning attentional learning method with recurrent neural network for proximity ranking metric embedding. The extensive experiments on two large-scale datasets show that our method achieves better performance than other state-of-the-art solutions to the problem.


Optica ◽  
2016 ◽  
Vol 3 (1) ◽  
pp. 64 ◽  
Author(s):  
Tae Joon Seok ◽  
Niels Quack ◽  
Sangyoon Han ◽  
Richard S. Muller ◽  
Ming C. Wu

Author(s):  
Kyungmok Kwon ◽  
Tae Joon Seok ◽  
Johannes Henriksson ◽  
Jianheng Luo ◽  
Ming C. Wu

Optica ◽  
2015 ◽  
Vol 2 (4) ◽  
pp. 370 ◽  
Author(s):  
Sangyoon Han ◽  
Tae Joon Seok ◽  
Niels Quack ◽  
Byung-Wook Yoo ◽  
Ming C. Wu

Author(s):  
Linjie Zhou ◽  
Liangjun Lu ◽  
Shuoyi Zhao ◽  
Zhanzhi Guo ◽  
Dong Li ◽  
...  

Author(s):  
Akhilesh S. P. Khope

In this paper, we review devices used in silicon photonic switches. Devices in switches are divided into active and passive devices. Active devices consist of microring resonator, contra directional couplers, mach zhender switches. Passive devices consist of waveguide crossings and arrayed waveguide gratings. We also list the state of the art in devices in a comparison table.


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