Low Barrier Nanomagnets as p-bits for Spin Logic

Abstract

It has recently been shown that a suitably interconnected network of tunable telegraphic noise generators or "p-bits" can be used to perform even precise arithmetic functions like a 32-bit adder. In this paper we use simulations based on the stochastic Landau-Lifshitz-Gilbert (sLLG) equation to demonstrate that similar impressive functions can be performed using unstable nanomagnets with energy barriers as low as a fraction of a kT. This is surprising since the magnetization of low barrier nanomagnets is not telegraphic with discrete values of +1 and -1. Rather it fluctuates randomly among all values between -1 and +1, and the output magnets are read with a thresholding device that translates all positive values to 1 and all negative values to zero. We present sLLG-based simulations demonstrating the operation of a 32-bit adder with a network of several hundred nanomagnets, exhibiting a remarkably precise correlation: The input magnets {A} and {B} as well as the output magnets {S} all fluctuate randomly and yet the quantity A+B-S is sharply peaked around zero! If we fix {A} and {B}, the sum magnets {S} rapidly converge to a unique state with S=A+B so that the system acts as an adder. But unlike standard adders, the operation is invertible. If we fix {S} and {B}, the remaining magnets {A} converge to the difference A=S-B. These examples suggest a new direction for the field of nanomagnetics away from stable high barrier magnets towards stochastic low barrier magnets which not only operate with lower currents, but are also more promising for continued downscaling.

This is the fourth in a series of papers on probabilistic spin logic (PSL). The earlier papers are: (1)Behin-Aein, Behtash, Vinh Diep, and Supriyo Datta. "A building block for hardware belief networks." Scientific Reports 6 (2016)., (2) Sutton, Brian, et al. "Intrinsic optimization using stochastic nanomagnets." Scientific Reports 7 (2017)., (3) Camsari et al. arXiv:1610.00377

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