12 citations · 23 across the 3 of their papers we have counts for
9 papers
Scalable variational Monte Carlo with graph neural ansatz
Li Yang, Wenjun Hu, Li Li
Deep neural networks have been shown as a potentially powerful ansatz in variational Monte Carlo for solving quantum many-body problems. We propose two improvements in this directi…
Origin of the Magnetic and Orbital ordering in -SrCrO
Bradraj Pandey, Yang Zhang, Nitin Kaushal +5
Motivated by recent experimental progress in transition metal oxides with the KNiF structure, we investigate the magnetic and orbital ordering in -SrCrO. Using f…
Similarities and differences between nickelate and cuprate films grown on a SrTiO substrate
Yang Zhang, Ling-Fang Lin, Wenjun Hu +3
The recent discovery of superconductivity in Sr-doped NdNiO films grown on SrTiO started a novel field within unconventional superconductivity. To understand the similariti…
Density Matrix Renormalization Group Study of Nematicity in Two Dimensions: Application to a Spin- Bilinear-Biquadratic Model on the Square Lattice
Wen-Jun Hu, Shou-Shu Gong, Hsin-Hua Lai +2
Nematic order is an exotic property observed in several strongly correlated systems, such as the iron-based superconductors. Using large-scale density matrix renormalization group…
Deep Learning-Enhanced Variational Monte Carlo Method for Quantum Many-Body Physics
Li Yang, Zhaoqi Leng, Guangyuan Yu +3
Artificial neural networks have been successfully incorporated into variational Monte Carlo method (VMC) to study quantum many-body systems. However, there have been few systematic…
Nematic and Antiferromagnetic Quantum Criticality in a Multi-Orbital Hubbard Model for Iron Pnictides
Wen-Jun Hu, Haoyu Hu, Rong Yu +4
The extent to which quantum criticality drives the physics of iron pnictides is a central question in the field. Earlier theoretical considerations were based on an effective field…