Ab initio calculation of real solids via neural network ansatz
Author
Abstract
Suggested Citation
DOI: 10.1038/s41467-022-35627-1
Download full text from publisher
References listed on IDEAS
- Sugiyama, G. & Zerah, G. & Alder, B.J., 1989. "Ground-state properties of metallic lithium," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 156(1), pages 144-168.
- Kenny Choo & Antonio Mezzacapo & Giuseppe Carleo, 2020. "Fermionic neural-network states for ab-initio electronic structure," Nature Communications, Nature, vol. 11(1), pages 1-7, December.
- George H. Booth & Andreas Grüneis & Georg Kresse & Ali Alavi, 2013. "Towards an exact description of electronic wavefunctions in real solids," Nature, Nature, vol. 493(7432), pages 365-370, January.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Michael Scherbela & Leon Gerard & Philipp Grohs, 2024. "Towards a transferable fermionic neural wavefunction for molecules," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
- Weiluo Ren & Weizhong Fu & Xiaojie Wu & Ji Chen, 2023. "Towards the ground state of molecules via diffusion Monte Carlo on neural networks," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Laura Lewis & Hsin-Yuan Huang & Viet T. Tran & Sebastian Lehner & Richard Kueng & John Preskill, 2024. "Improved machine learning algorithm for predicting ground state properties," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
- Lennart Dabelow & Masahito Ueda, 2022. "Three learning stages and accuracy–efficiency tradeoff of restricted Boltzmann machines," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
- Huziel E. Sauceda & Luis E. Gálvez-González & Stefan Chmiela & Lauro Oliver Paz-Borbón & Klaus-Robert Müller & Alexandre Tkatchenko, 2022. "BIGDML—Towards accurate quantum machine learning force fields for materials," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35627-1. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.