Metrics for spin-based computing

doi:10.1038/s42254-025-00918-1

Metrics for spin-based computing

2026-02-27

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Karin Everschor‐Sitte

DOI：10.1038/s42254-025-00918-1

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Spin-based computing is emerging as a powerful approach for energy-efficient and high-performance solutions to future data processing hardware. Spintronic devices function by electrically manipulating the collective dynamics of the electron spin, which is inherently non-volatile, nonlinear and fast operating, and can couple to other degrees of freedom such as photonic and phononic systems. This Technical Review explores key advances in integrating magnetic and spintronic elements into computational architectures, ranging from fundamental components such as radiofrequency neurons or synapses and spintronic probabilistic bits to broader frameworks such as reservoir computing and magnetic Ising machines. For each of these systems, we discuss hardware-specific and task-dependent metrics to evaluate their computing performance and evaluate the physical processes that need to be optimized to increase performance. Finally, we discuss challenges and future opportunities, highlighting the potential of spin-based computing in next-generation technologies. A number of different platforms for spin-based computing have emerged over the past few years, offering energy-efficient computing methods. This Technical Review identifies key metrics that must be evaluated to benchmark their performance.

Keywords:

Electrical and electronic engineering

Spintronics

Physics

general

Metrics for spin-based computing

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