[2309.06579] Compact and Low-Loss PCM-based Silicon Photonic MZIs for Photonic Neural Networks
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Computer Science > Emerging Technologies

arXiv:2309.06579 (cs)
[Submitted on 18 Aug 2023]

Title:Compact and Low-Loss PCM-based Silicon Photonic MZIs for Photonic Neural Networks

Authors:Amin Shafiee, Sanmitra Banerjee, Benoit Charbonnier, Sudeep Pasricha, Mahdi Nikdast
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Abstract:We present an optimized Mach-Zehnder Interferometer (MZI) with phase change materials for photonic neural networks (PNNs). With 0.2 dB loss, -38 dB crosstalk, and length of 52 micrometer, the designed MZI significantly improves the scalability and accuracy of PNNs under loss and crosstalk.
Comments: This paper is accepted at IEEE Photonics Conference (IPC) 2023
Subjects: Emerging Technologies (cs.ET); Applied Physics (physics.app-ph)
Cite as: arXiv:2309.06579 [cs.ET]
  (or arXiv:2309.06579v1 [cs.ET] for this version)
  https://doi.org/10.48550/arXiv.2309.06579

Submission history

From: Mahdi Nikdast [view email]
[v1] Fri, 18 Aug 2023 02:40:12 UTC (2,768 KB)
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