Neuromorphic Optical Data Storage Enabled by Nanophotonics: A Perspective
Simone Lamon, Qiming Zhang, Haoyi Yu, Min Gu
Abstract
The development of cloud computing and artificial intelligence technology has increased data storage demands, causing an urgency to progress nanophotonics-enabled optical data storage. Inspiration can be taken from the working principles of the brain's memory that has high storage capacity and parallelism, integration between data storage and processing with self-learning ability, and low-power consumption. The correlation between the emerging neuroscience concept of cell engrams as the basic units of the brain's memory and nanophotonics techniques and materials can aid the development of neuromorphic optical data storage enabled by nanophotonics toward higher storage capacity and throughput and lower energy consumption. In this perspective, we explore the feasibility of a nanophotonics counterpart to biology by emulating the brain's memory based on cell engrams toward nanophotonics-enabled neuromorphic optical data storage. We overview emerging nanophotonics techniques and materials, as well as the challenges and opportunities of such an implementation for the future of optical data storage enabled by nanophotonics.