Differentiable programming tensor networks for Kitaev magnets

doi:10.1103/PhysRevB.108.085103

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	Differentiable programming tensor networks for Kitaev magnets
	Zhang, Xing -Yu ; Liang, Shuang ; Liao, Hai-Jun ; Li, Wei 3,4; Wang, Lei 2
刊名	PHYSICAL REVIEW B
	2023
卷号	108 期号:8 页码:85103
关键词	MATRIX ALGORITHM
ISSN号	2469-9950
DOI	10.1103/PhysRevB.108.085103
英文摘要	We present a general computational framework to investigate ground-state properties of quantum spin models on infinite two-dimensional lattices using automatic differentiation-based gradient optimization of infinite projected entangled-pair states. The approach exploits the variational uniform matrix product states to contract infinite tensor networks with unit cell structure and incorporates automatic differentiation to optimize the local tensors. We applied this framework to the Kitaev-type model, which involves complex interactions and competing ground states. To evaluate the accuracy of this method, we compared the results with exact solutions for the Kitaev model and found that it has a better agreement for various observables compared to previous tensor network calculations based on imaginary-time projection. Additionally, by finding out the ground state with lower variational energy compared to previous studies, we provided convincing evidence for the existence of nematic paramagnetic phases and 18-site configuration in the phase diagram of the K -F model. Furthermore, in the case of the realistic K -J -F -F' model for the Kitaev material a-RuCl3, we discovered a noncollinear zigzag ground state. Lastly, we also find that the strength of the critical out-of-plane magnetic field that suppresses such a zigzag state has a lower transition field value than the previous finite-cylinder calculations. The framework is versatile and will be useful for a quick scan of phase diagrams for a broad class of quantum spin models.
学科主题	Materials Science ; Physics
语种	英语
内容类型	期刊论文
源URL	[http://ir.itp.ac.cn/handle/311006/27962]
专题	理论物理研究所_理论物理所1978-2010年知识产出
作者单位	1.Chinese Acad Sci, Inst Phys, Beijing 100190, Peoples R China 2.Univ Sci & Technol Beijing, Dept Phys, Beijing 100080, Peoples R China 3.Songshan Lake Mat Lab, Dongguan 523808, Guangdong, Peoples R China 4.Chinese Acad Sci, Inst Theoret Phys, Beijing 100190, Peoples R China 5.Chinese Acad Sci, Ctr Excellence Topol Quantum Computat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Xing -Yu,Liang, Shuang,Liao, Hai-Jun,et al. Differentiable programming tensor networks for Kitaev magnets[J]. PHYSICAL REVIEW B,2023,108(8):85103.
APA	Zhang, Xing -Yu,Liang, Shuang,Liao, Hai-Jun,Li, Wei,&Wang, Lei.(2023).Differentiable programming tensor networks for Kitaev magnets.PHYSICAL REVIEW B,108(8),85103.
MLA	Zhang, Xing -Yu,et al."Differentiable programming tensor networks for Kitaev magnets".PHYSICAL REVIEW B 108.8(2023):85103.