Theoretical condensed matter physics and computational materials physics [T(CMP)2] laboratory at University of Chinese Academy of Sciences (UCAS) is primarily devoted to studying theoretically the basic issues involved in condensed matter physics and materials science.
Condensed matter physics is the science that deals with the structures, properties and fundamental laws of condensed matter. It is connecting atomic-scale physics to the properties of macroscopic systems or everyday things. The essence of the subject can be revealed in ten words: "The whole is more than the sum of its parts." The emergent phenomena are its main themes of exploration.
By invoking experimental, theoretical and computational methods, people push forward the advances of condensed matter physics through expected and unexpected discoveries, understanding exotic phenomena as well as properties of new materials, and so forth. Thus, condensed matter physics and materials physics are the twin subjects in physics. It is known that condensed matter physics and materials physics stands in the center of revolutionary advances in wide fields of science and technology. On the other hand, condensed matter physics and materials physics are full of excitements, a lot of unknowns, marvelous discoveries, conceptual breakthroughs, and so on, which quite deserve to explore.
Our research fields involve with strongly correlated fermion and boson systems, superconductivity, superfluidity, quantum magnetism, molecular magnetism, spintronics, computational materials physics, mesoscopic physics, statistical physics, nanoscience, clean energy, quantum information and computation, etc.
The modern analytical and numerical methods in condensed matter physics are applied or proposed in our research, including bosonization, fermionization, conformal field theory, non-equilibrium Green function, various mean-field, quantum Monte Carlo, density-matrix renormalization group and variants, linearized tensor network renormalization group, DFT calculations, etc. The computing facility with HPC clusters of 320 nodes is available, and the supercomputing resources in China can also be used.