This study employs computational intelligence techniques to optimize complex photonic devices. Traditional surrogate models have limitations in accurately modeling complex devices like vortex phase masks (VPMs). VPMs are essential for observing faint light sources near bright objects, such as exoplanets near stars. To address this, a data-efficient surrogate optimization setup using a deep neural network (U-Net) and particle swarm optimization is proposed. The U-Net achieves high accuracy and efficiency. The resulting surrogate optimization setup outperforms both carefully devised grid-based searches and optimizers.
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.