# Engineering Relaxation Pathways in Building Blocks of Artificial Spin Ice for Computation

## TL;DR

This paper explores how engineered arrangements of thermally-active nanomagnets in artificial spin ice can perform both deterministic and probabilistic computation by controlling relaxation pathways and intermagnet distances.

## Contribution

It introduces a method to engineer thermal relaxation pathways in artificial spin ice for computation and demonstrates tuning of output probabilities and interconnected computational blocks.

## Key findings

- Engineered relaxation pathways enable deterministic and probabilistic computation.
- Adjusting intermagnet distance tunes the probability of specific outcomes.
- Connected building blocks demonstrate potential for complex computation.

## Abstract

Nanomagnetic logic, which makes use of arrays of dipolar-coupled single domain nanomagnets for computation, holds promise as a low power alternative to traditional computation with CMOS. Beyond the use of nanomagnets for Boolean logic, nanomagnets can also be exploited for non-deterministic computational schemes such as edge detection in images and for solving the traveling salesman problem. Here, we demonstrate the potential of arrangements of thermally-active nanomagnets based on artificial spin ice for both deterministic and probabilistic computation. This is achieved by engineering structures that follow particular thermal relaxation pathway consisting of a sequence of reorientations of magnet moments from an initial field-set state to a final low energy output state. Additionally, we demonstrate that it is possible to tune the probability of attaining a particular final low-energy state, and therefore the likelihood of a given output, by modifying the intermagnet distance. Finally, we experimentally demonstrate a scheme to connect several computational building blocks for complex computation.

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Source: https://tomesphere.com/paper/1812.06936