首页|Findings from Department of Physics in Machine Learning Reported (Classification of Skyrmionic Textures and Extraction of Hamiltonian Parameters Via Machine Lea rning)
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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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.”
HangzhouPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningDepartment of Physics
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