Machine learning study of the deformed one-dimensional topological superconductor
| Autor: | Jae Hyuck Lee, Hyun C. Lee |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer Science::Machine Learning
010302 applied physics Superconductivity Zero mode Artificial neural network business.industry Computer science General Physics and Astronomy 02 engineering and technology Link (geometry) 021001 nanoscience & nanotechnology Topology Machine learning computer.software_genre 01 natural sciences Convolutional neural network MAJORANA 0103 physical sciences Artificial intelligence 0210 nano-technology business computer Supervised training |
| Zdroj: | Journal of the Korean Physical Society. 79:173-184 |
| ISSN: | 1976-8524 0374-4884 |
| DOI: | 10.1007/s40042-021-00180-5 |
| Popis: | A one-dimensional p-wave topological superconductor deformed by a sine-square-deformation is studied in the framework of machine learning. A supervised learning algorithm is applied with a convolutional neural network to discern the existence of a Majorana zero mode, which is the hallmark of topological superconductivity. The machine learning algorithm learns features of the Majorana zero mode, and the neural network trained with the dataset from the link deformed case turns out to be the most effective. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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