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このアイテムのファイル:
| ファイル | 記述 | サイズ | フォーマット | |
|---|---|---|---|---|
| PhysRevResearch.5.033189.pdf | 8.5 MB | Adobe PDF | 見る/開く |
| タイトル: | Multi-body wave function of ground and low-lying excited states using unornamented deep neural networks |
| 著者: | Naito, Tomoya Naito, Hisashi Hashimoto, Koji    https://orcid.org/0000-0001-5619-9096 (unconfirmed) |
| 著者名の別形: | 内藤, 智也 内藤, 久資 橋本, 幸士 |
| キーワード: | Few-body systems Quantum many-body systems Deep learning Machine learning Variational approach Variational wave functional methods Interdisciplinary Physics |
| 発行日: | Sep-2023 |
| 出版者: | American Physical Society (APS) |
| 誌名: | Physical Review Research |
| 巻: | 5 |
| 号: | 3 |
| 論文番号: | 033189 |
| 抄録: | We propose a method to calculate wave functions and energies not only of the ground state but also of low-lying excited states using a deep neural network and the unsupervised machine learning technique. For systems composed of identical particles, a simple method to perform symmetrization for bosonic systems and antisymmetrization for fermionic systems is also proposed. |
| 著作権等: | Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. |
| URI: | http://hdl.handle.net/2433/286739 |
| DOI(出版社版): | 10.1103/PhysRevResearch.5.033189 |
| 出現コレクション: | 学術雑誌掲載論文等 |
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