activity
20182022
collaborators

8 papers

cs.RO2022

Learning Autonomous Vehicle Safety Concepts from Demonstrations

Karen Leung, Sushant Veer, Edward Schmerling +1

Evaluating the safety of an autonomous vehicle (AV) depends on the behavior of surrounding agents which can be heavily influenced by factors such as environmental context and infor…

cond-mat.str-el2022

A quantum spin liquid phase in the Kitaev-Hubbard model

Shaojun Dong, Hao Zhang, Chao Wang +3

The quantum spin liquid (QSL) state has been searched intensively in Kitaev-like materials, such as the Iridium oxides IrO and -RuCl. The half-filled Kitaev-Hubbard…

cond-mat.str-el2020

Hybrid convolutional neural network and PEPS wave functions for quantum many-particle states

Xiao Liang, Shao-Jun Dong, Lixin He

Neural networks have been used as variational wave functions for quantum many-particle problems. It has been shown that the correct sign structure is crucial to obtain the high acc…

cond-mat.str-el2019

Reply to comments on "Gapless spin liquid ground state of spin-1/2 - Heisenberg model on square lattices"

Wen-Yuan Liu, Shaojun Dong, Chao Wang +4

In a recent comments [arXiv:1909.12788 (2019)], Zhao et al. argue that the definition of dimer orders used in our paper [Phys. Rev. B 98, 241109 (2018)] may not rule out valence bo…

cond-mat.str-el2019

Stable diagonal stripes in the t-J model at =1/8 doping from fPEPS calculations

Shao-Jun Dong, Chao Wang, Yong-Jian Han +2

We investigate the 2D t-J model at a hole doping of =1/8 using recently developed high accuracy fermionic projected entangled pair states(fPEPS) method. By applying stoc…

cond-mat.str-el2018

Gradient optimization of fermionic projected entangled pair states on directed lattices

Shao-Jun Dong, Chao Wang, Yongjian Han +2

The recently developed stochastic gradient method combined with Monte Carlo sampling techniques [PRB {\bf 95}, 195154 (2017)] offers a low scaling and accurate method to optimize t…