597 citations · 6.3k across the 117 of their papers we have counts for
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Self-Learning Determinantal Quantum Monte Carlo Method
Xiao Yan Xu, Yang Qi, Junwei Liu +2
Self-learning Monte Carlo method [arXiv:1610.03137, 1611.09364] is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we i…
Non-Fermi-liquid at (2+1)d ferromagnetic quantum critical point
Xiao Yan Xu, Kai Sun, Yoni Schattner +2
We construct a two-dimensional lattice model of fermions coupled to Ising ferromagnetic critical fluctuations. Using extensive sign-problem-free quantum Monte Carlo simulations, we…
Self-Learning Monte Carlo Method in Fermion Systems
Junwei Liu, Huitao Shen, Yang Qi +2
We develop the self-learning Monte Carlo (SLMC) method, a general-purpose numerical method recently introduced to simulate many-body systems, for studying interacting fermion syste…
The amplitude mode in three-dimensional dimerized antiferromagnets
Yan Qi Qin, Bruce Normand, Anders Sandvik +1
The amplitude (Higgs) mode is a ubiquitous collective excitation related to spontaneous breaking of a continuous symmetry. We combine quantum Monte Carlo (QMC) simulations with sto…
Self-Learning Monte Carlo Method
Junwei Liu, Yang Qi, Zi Yang Meng +1
Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of general and efficient update algori…
Effect of nematic order on the low-energy spin fluctuations in detwinned BaFeNiAs
Wenliang Zhang, J. T. Park, Xingye Lu +8
The origin of nematic order remains one of the major debates in iron-based superconductors. In theories based on spin nematicity, one major prediction is that the spin-spin correla…