In the past decade, the field of neuromorphic photonics has experienced significant growth. To extend the reach of this technology, researchers continue to push the limits of these systems with respect to network size and bandwidth. However, without proper RF-optimized architectural designs, as operating frequencies are scaled up, significant losses of RF power can be incurred at each neuron. Within the broadcast and weight neuromorphic photonic architecture, this excess loss will be accumulated until processing is no longer feasible. If designed properly, RF loss can be minimized significantly, and residual loss could be compensated by cointegrated transimpedance amplifiers, thus enabling further scaling of the network. In this paper, the authors present broadband weighting of RF input signals with a 3-dB bandwidth of 4.28 GHz, utilizing the linear front-end of a silicon photonic neural network. Additionally, the authors present link loss measurements and analysis.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.