Spintronics probabilistic computer

Realization of proposals by Feynman and Hinton utilizing a spintronics device

Abstract

In 1981, Feynman proposed a computer that operates probabilistically at the hardware level, along with the concept of quantum computers. Boltzmann machine learning proposed by Hinton et al., 2024 Nobel laureate in physics, also models a magnetic system consisting of probabilistically fluctuating spins. As the increasing power consumption associated with the widespread use of artificial intelligence becomes a pressing challenge, this paper discusses spintronics probabilistic computers that naturally realize the proposals of Feynman and Hinton, enabling energy-efficient artificial intelligence computation. Proof-of-concepts including combinatorial optimization, machine learning, and quantum simulation, as well as the development of superparamagnetic tunnel junction devices for enhancing computing performance are described.