Article 5XNB1 Printing Circuits on Rare Nanomagnets Puts a New Spin on Computing

Printing Circuits on Rare Nanomagnets Puts a New Spin on Computing

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Printing circuits on rare nanomagnets puts a new spin on computing:

New research artificially creating a rare form of matter known as spin glass could spark a new paradigm in artificial intelligence by allowing algorithms to be directly printed as physical hardware. The unusual properties of spin glass enable a form of AI that can recognize objects from partial images much like the brain does and show promise for low-power computing, among other intriguing capabilities.

"Our work accomplished the first experimental realization of an artificial spin glass consisting of nanomagnets arranged to replicate a neural network," said Michael Saccone, a post-doctoral researcher in theoretical physics at Los Alamos National Laboratory and lead author of the new paper in Nature Physics. "Our paper lays the groundwork we need to use these physical systems practically."

[...] At the intersection of engineered materials and computation, spin-glass systems are a type of disordered system of nanomagnets arising from random interactions and competition between two types of magnetic order in the material. They exhibit "frustration," meaning that they don't settle into a uniformly ordered configuration when their temperature drops, and they possess distinct thermodynamic and dynamic traits that can be harnessed for computing applications.

"Theoretical models describing spin glasses are broadly used in other complex systems, such as those describing brain function, error-correcting codes or stock-market dynamics," Saccone said. "This wide interest in spin glasses provides strong motivation to generate an artificial spin glass."

The research team combined theoretical and experimental work to fabricate and observe the artificial spin glass as a proof-of-principle Hopfield neural network, which mathematically models associative memory to guide the disorder of the artificial spin systems.

Journal Reference:
Saccone, Michael, Caravelli, Francesco, Hofhuis, Kevin, et al. Direct observation of a dynamical glass transition in a nanomagnetic artificial Hopfield network, Nature Physics (DOI: 10.1038/s41567-022-01538-7)

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