Robotics & Machine Learning Daily News2024,Issue(MAY.1) :30-31.

Findings from Department of Physics in Machine Learning Reported (Classification of Skyrmionic Textures and Extraction of Hamiltonian Parameters Via Machine Lea rning)

Robotics & Machine Learning Daily News2024,Issue(MAY.1) :30-31.

Findings from Department of Physics in Machine Learning Reported (Classification of Skyrmionic Textures and Extraction of Hamiltonian Parameters Via Machine Lea rning)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Machine Learning are pre sented in a new report. According to newsreporting originating from Hangzhou, P eople’s Republic of China, by NewsRx correspondents, researchstated, “Classifyi ng skyrmionic textures and extracting magnetic Hamiltonian parameters represent crucialand challenging pursuits within the realm of two-dimensional (2D) spintr onics. In this study, we leveragemicromagnetic simulation and machine learning (ML) to theoretically achieve the recognition of ninedistinct skyrmionic textur es and the extraction of magnetic Hamiltonian parameters from extensive spintex ture images in a 2D Heisenberg model.”

Key words

Hangzhou/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Department of Physics

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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