Neuromorphic Spintronics
This work addresses the problem of improving computational efficiency for technology applications, but it is incremental as it reviews and synthesizes existing concepts without presenting new experimental results.
The authors tackled the challenge of creating brain-inspired, efficient computing systems by combining neuromorphic computing and spintronics, highlighting examples like artificial neural networks and reservoir computing that could revolutionize computational efficiency and functionality.
Neuromorphic spintronics combines two advanced fields in technology, neuromorphic computing and spintronics, to create brain-inspired, efficient computing systems that leverage the unique properties of the electron's spin. In this book chapter, we first introduce both fields - neuromorphic computing and spintronics and then make a case for neuromorphic spintronics. We discuss concrete examples of neuromorphic spintronics, including computing based on fluctuations, artificial neural networks, and reservoir computing, highlighting their potential to revolutionize computational efficiency and functionality.