SPICE Workshop on Quantum Functionalities of Nanomagnets, June 17th - 19th 2025
Paula Mellado
Conventional approaches to computing with nanomagnets require an initial state, and a final state corresponding to an expected outcome. Assuming a single spin-flip regime, an energetic relaxation from the initialized state to that of a final low-energy state will include intermediate states with variable magnetostatic energies, which affect the probability of an outcome. Here, we investigate intermediate states in a simple nanomagnet toy model of four nanomagnets arranged onto a square plaquette. In doing so, we can systematically demonstrate design approaches to mitigate (or leverage) computational “errors” in artificial spin ice-inspired computational logic. We reveal an explicit relation between geometry and energetics through multipolar analysis and comment specifically on the nature of energy relaxation pathways that could directly affect the designing of logic units for conventional and unconventional computing applications. We support our theoretical models with experimental results on field-induced relaxation using Magnetic Force Microscopy measurements. Our work provides an intuitive way to design logic elements for future computing applications with artificial spin ice structures.