Photonic emergent Learning

Abstract

Disordered, self-assembled media, contain a large amount of information, which can be seen as a huge set of random and uncontrolled memory patterns. In the framework of optics, in which an opaque medium may modelled with the transmission matrix approach, each transmitted mode “contains” a memory element which is embodied by the correspondent transmission vector. Even if the stored amount of information in this system is huge, these random memories cannot be tailored easily. Here we present a new approach to write, read, and classify memory patterns: the photonic emergent learning. The writing paradigm is borrowed form a-physical- mathematical model for the biological memory, the emergent archetype, which we translated to photonics. In our approach the random patterns enclosed in the transmitted electromagnetic modes, are used as prototypes which are summed in constructive fashion in order write our target archetype-memory into our disordered optical memory (DOM). The DOM can work as a content addressable memory, retrieving at the lightning speed which memory in the library is the closest to an optically proposed query pattern. Moreover, the optical memories can be organized into super structures containing memories of the same thus efficiently delivering a classification task.