تقرير
Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning
| العنوان: | Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning |
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| المؤلفون: | Mamada, Naoya, Mizumaki, Masaichiro, Akai, Ichiro, Aonishi, Toru |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science Condensed Matter |
| مصطلحات موضوعية: | Condensed Matter - Materials Science, Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | We estimate the spatial distribution of heterogeneous physical parameters involved in the formation of magnetic domain patterns of polycrystalline thin films by using convolutional neural networks. We propose a method to obtain a spatial map of physical parameters by estimating the parameters from patterns within a small subregion window of the full magnetic domain and subsequently shifting this window. To enhance the accuracy of parameter estimation in such subregions, we employ large-scale models utilized for natural image classification and exploit the benefits of pretraining. Using a model with high estimation accuracy on these subregions, we conduct inference on simulation data featuring spatially varying parameters and demonstrate the capability to detect such parameter variations. Comment: 32 pages, 14 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2305.14764 |
| رقم الأكسشن: | edsarx.2305.14764 |
| قاعدة البيانات: | arXiv |
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