activity
20102023
most citedLinearized Tensor Renormalization Group Algorithm for Thermodynamics of Quantum Lattice Models

100 citations · 520 across the 25 of their papers we have counts for

collaborators

25 papers

cond-mat.mes-hall2023★ 1 cited

Slonczewski-spin-current driven dynamics of 180 domain walls in spin valves with interfacial Dzyaloshinskii-Moriya interaction

Jiaxin Du, Mei Li, Xue Zhang +4

Steady-flow dynamics of ferromagnetic 180 domain walls (180DWs) in long and narrow spin valves (LNSVs) with interfacial Dzyaloshinskii-Moriya interaction (IDMI) under spi…

cond-mat.mes-hall2022★ 1 cited

Ground states and magnonics in orthogonally-coupled symmetric all-antiferromagnetic junctions

Mei Li, Bin Xi, Wei He +2

In this work, the rich ground-state structure of orthogonally-coupled symmetric all-antiferromagnetic junctions with easy-plane anisotropy is reported. Spin reorientation process r…

stat.ML2022

Deep Machine Learning Reconstructing Lattice Topology with Strong Thermal Fluctuations

Xiao-Han Wang, Pei Shi, Bin Xi +2

Applying artificial intelligence to scientific problems (namely AI for science) is currently under hot debate. However, the scientific problems differ much from the conventional on…

cond-mat.other2022★ 23 cited

Triple-meron crystal in high-spin Kitaev magnets

Ken Chen, Qiang Luo, Zongsheng Zhou +5

Spin textures with nontrivial topology hold great promise in future spintronics applications since they are robust against local deformations. The meron, as one of such spin textur…

cond-mat.mes-hall2021★ 2 cited

Chiral domain wall dynamics in magnetic heterostructures with bulk Dzyaloshinskii-Moriya interactions

Mei Li, Bin Xi, Jie Lu +1

In this work, dynamics of chiral domain walls in long and narrow magnetic heterostructures based on non-centrosymmetric chiral magnets with bulk Dzyaloshinskii-Moriya interactions…

quant-ph2021★ 1 cited

Predicting Quantum Potentials by Deep Neural Network and Metropolis Sampling

Rui Hong, Peng-Fei Zhou, Bin Xi +3

The hybridizations of machine learning and quantum physics have caused essential impacts to the methodology in both fields. Inspired by quantum potential neural network, we here pr…