We are interested in various topics in theoretical condensed matter physics, with a focus on but not limited to emergent phenomena and innovative algorithms in quantum many-body systems.
Machine learning approach to quantum many-body systems
Machine learning quantum phases of matter
Machine learning for quantum controls and computations
Machine learning experimental and numerical big data
Topological phases and materials
Symmetry-protected topological insulators
Strongly-correlated Abelian and non-Abelian topological order and quantum spin liquids
Weyl and Dirac semi-metals
Quantum entanglement approach to strongly-correlated systems
Minimum entropy states
Quantum state tomography
Entanglement entropy and spectrum for nontrivial quantum liquids
Transport signatures in realistic materials
Quantum oscillations and magneto-transport in Weyl and Dirac semimetals
Transport in charge density waves, bilayer structures, nematicity, etc.
Effective theory of quasi-periodic systems and cyclotron electrons
Other computational methods
Variational Monte Carlo and Quantum Monte Carlo methods
Recursive Green's function method
Tensor network state method
Exact diagonalization method