首页    期刊浏览 2024年07月09日 星期二
登录注册

文章基本信息

  • 标题:Author Correction: Learning spin liquids on a honeycomb lattice with artificial neural networks
  • 本地全文:下载
  • 作者:Chang‑Xiao Li ; Sheng Yang ; Jing‑Bo Xu
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2021
  • 卷号:11
  • DOI:10.1038/s41598-021-02472-z
  • 语种:English
  • 出版社:Springer Nature
  • 摘要:Correction to: Scientific Reports https://doi.org/10.1038/s41598-021-95523-4, published online: 17 August 2021 This original version of this Article contained an error, as the paper did not discuss the related work of Noormandipour et al. (2021). As a result, Reference 52 was omitted and is listed below, Noormandipour, M., Sun, Y. & Haghighat, B. Restricted boltzmann machine representation for the groundstate and excited states of kitaev honeycomb model. https://arxiv.org/abs/2003.07280 (2021) In addition, the text in the Conclusion and discussion, “By investigating the accuracy of the learned energy and structure factor, we first confirmed the validity of the machine learning method in solving the QSL honeycomb lattice.” now reads: “We note that a previous study 52 has examined the capability of RBMs to find ground-state energy of the Kitaev honeycomb model. However, they only focus on the specific parameter choice \documentclass[12pt
国家哲学社会科学文献中心版权所有