Our group pursues theoretical understanding and calculations in spintronics and neuromorphic computing, especially spintronics-based approaches to neuromorphic computing. Approaches vary from quasi-analytic to computationally intensive, as appropriate. Particular approaches to biologically-inspired computing include reservior computing, stoschastic and probablistic computing, race logic, memristors, and novel algorithms. Work in spintronics has recently concentrated on spin transfer torques, spin-orbit torques, and other novel ways to amnipulate the magentization.
Some of this work is illustrated in publications:
Overcoming device unreliability with continuous learning in a population coding based computing system, A. Mizrahi, J. Grollier, D. Querlioz, and M. D. Stiles, J. Appl. Phys. 124, 152111 (2018).
Spintronic Nanodevices for Bioinspired Computing, J. Grollier, D. Querlioz, M. D. Stiles, Proc. IEEE, 104, 2024 (2016).
Spin transport at interfaces with spin-orbit coupling: Phenomenology, V. P. Amin and M. D. Stiles, Phys. Rev. B 94, 104420 (2016).
Electron transport; Electronic structure; Magnetism; Nanotechnology; Spintronics; Neuromorphic Computing