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arXiv · 2211.12903

Searching for Possible Spin Configurations of Ferrum Chain via Quantum Approximate Optimization Algorithm

Saba Arife Bozpolat
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Abstract

Calculating the expected spin configuration of the chain consisting of Ferrum atoms interacting with each other through exchange interaction is fundamentally a configuration optimization problem. Quantum Approximate Optimization Algorithm is a suitable candidate to configure such systems on a quantum device. In this work we have considered Ferrum chains of three different lengths and calculated their most-probable spin configurations using Quantum Approximate Optimization Algorithm. We employed a Quantum Feed Forward Neural Network as the optimizer of Quantum Approximate Optimization Algorithm. We have successfully obtained the expected spin configuration for the longest Ferrum Chain.

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Saba Arife Bozpolat. 2022-11-23. Searching for Possible Spin Configurations of Ferrum Chain via Quantum Approximate Optimization Algorithm. https://arxiv.org/abs/2211.12903

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