High accuracy single-layer free-space diffractive neuromorphic classifiers for spatially incoherent light
Abstract
Free-space all-optical diffractive systems have shown promise for neuromorphic classification of objects without converting light to the electronic domain. While the factors that govern these systems have been studied for coherent light, the fundamental properties for incoherent light have not been addressed, despite the importance for many applications. Here we use a co-design approach to show that optimized systems for spatially incoherent light can achieve performance on par with the best linear electronic classifiers even with a single layer containing few diffractive features. This performance is limited by the inherent linear nature of incoherent optical detection. We circumvent this limit by using a differential detection scheme that achieves greater than 94% classification accuracy on the MNIST dataset and greater than 85% classification accuracy for Fashion-MNIST, using a single layer metamaterial.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 29, 2022
- Source ID
- 10.1364/oe.455007
Entities
People
- Corinne M. Teeter
- Craig M. Vineyard
- Elliot J. Fuller
- François Léonard
Organizations
- Defense Advanced Research Projects Agency
- Sandia National Laboratories