Details
Original language | English |
---|---|
Article number | 020502 |
Journal | Revista Mexicana de Fisica |
Volume | 69 |
Issue number | 2 |
Publication status | Published - 1 Mar 2023 |
Externally published | Yes |
Abstract
The use of machine learning algorithms to address classification problems in several scientific branches has increased over the past years. In particular, the supervised learning technique with artificial neural networks has been successfully employed in classifying phases of matter. In this article, we use a fully connected feed-forward neural network to classify extended and localized single-particle states that arise from quasiperiodic one-dimensional lattices.
Keywords
- Algorithms, Hamiltonian, single-particle states
ASJC Scopus subject areas
- Physics and Astronomy(all)
- General Physics and Astronomy
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Revista Mexicana de Fisica, Vol. 69, No. 2, 020502, 01.03.2023.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Artificial neural network for the single-particle localization problem in quasiperiodic one-dimensional lattices
AU - Domínguez-Castro, G. A.
AU - Paredes, R.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - The use of machine learning algorithms to address classification problems in several scientific branches has increased over the past years. In particular, the supervised learning technique with artificial neural networks has been successfully employed in classifying phases of matter. In this article, we use a fully connected feed-forward neural network to classify extended and localized single-particle states that arise from quasiperiodic one-dimensional lattices.
AB - The use of machine learning algorithms to address classification problems in several scientific branches has increased over the past years. In particular, the supervised learning technique with artificial neural networks has been successfully employed in classifying phases of matter. In this article, we use a fully connected feed-forward neural network to classify extended and localized single-particle states that arise from quasiperiodic one-dimensional lattices.
KW - Algorithms
KW - Hamiltonian
KW - single-particle states
UR - http://www.scopus.com/inward/record.url?scp=85150251974&partnerID=8YFLogxK
U2 - 10.31349/RevMexFis.69.020502
DO - 10.31349/RevMexFis.69.020502
M3 - Article
AN - SCOPUS:85150251974
VL - 69
JO - Revista Mexicana de Fisica
JF - Revista Mexicana de Fisica
SN - 0035-001X
IS - 2
M1 - 020502
ER -