Xiao Yan Xu

Self-learning quantum Monte Carlo method in interacting fermion systems

Self-learning Monte Carlo method [1, 2] is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we implement this method in the framework of determinantal quantum Monte Carlo simulation of interacting fermion systems. Guided by a self-learned bosonic effective action, our method uses a cumulative update [2] algorithm to sample auxiliary field configurations quickly and efficiently. We demonstrate that self-learning determinantal Monte Carlo method can reduce the auto-correlation time to as short as one near a critical point, leading to O(N)-fold speedup. This enables to simulate interacting fermion system on a 100×100 lattice for the first time, and obtain critical exponents with high accuracy.

Non-Fermi Liquid at ( 2+1 ) D Ferromagnetic Quantum Critical Point

The behavior of electrons near quantum critical points, such as magnetic phase transitions at temperatures approaching absolute zero, are of vital interest but are extremely challenging to understand. New computer simulations solve this problem, exactly, for one example of these strange metals and reveal a new type of quantum critical point.

Competing pairing channels in the doped honeycomb lattice Hubbard model

Proposals for superconductivity emerging from correlated electrons in the doped Hubbard model on the honeycomb lattice range from chiral

Mott transition in the triangular lattice Hubbard model : A dynamical cluster approximation study

d+id

Topological phase transitions with SO(4) symmetry in (2+1)d interacting Dirac fermions

singlet to

Dynamical Generation of Topological Masses in Dirac Fermions

p+ip

Symmetry-enforced self-learning Monte Carlo method applied to the Holstein model

triplet pairing, depending on the considered range of doping and interaction strength, as well as the approach used to analyze the pairing instabilities. Here, we consider these scenarios using large-scale dynamic cluster approximation (DCA) calculations to examine the evolution in the leading pairing symmetry from weak to intermediate coupling strength. These calculations focus on doping levels around the van Hove singularity (VHS) and are performed using DCA simulations with an interaction-expansion continuous-time quantum Monte Carlo cluster solver. We calculated explicitly the temperature dependence of different uniform superconducting pairing susceptibilities and found a consistent picture emerging upon gradually increasing the cluster size: while at weak coupling the

Itinerant quantum critical point with frustration and non-Fermi-liquid

d+id

EMUS-QMC: Elective Momentum Ultra-Size Quantum Monte Carlo Method

singlet pairing dominates close to the VHS filling, an enhanced tendency towards

Non-Fermi-liquid at (2+1)d ferromagnetic quantum critical point

p