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Machine learning study of the deformed one-dimensional topological superconductor
- Source :
- Journal of the Korean Physical Society. 79:173-184
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- 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.
- Subjects :
- 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
Subjects
Details
- ISSN :
- 19768524 and 03744884
- Volume :
- 79
- Database :
- OpenAIRE
- Journal :
- Journal of the Korean Physical Society
- Accession number :
- edsair.doi...........a3df8b10546ec6ddbc450b85b6f694d5