Magnetism and metal-insulator transition in nickel oxide from Auxiliary-Field Quantum Monte Carlo (AFQMC) studies

NiO is of great interests in condensed matter physics. Within single particle mean-field framework, one can obtain its insulating anti-ferromagnetic ground state and correct band gap, magnetic momentum, or lattice constant by adjusting exchange correlation interactions. However, it is challenging to re-produce all the properties using the same setup, and the predicted magnetic and metallic transitions are questionable. It demands physically accurate and computationally efficient many-body algorithms to tackle these questions. AFQMC works in second quantized representation and has been shown promising in solving extended systems with high accuracy [comparable to those of CCSD(T) and FCI] and low scaling (N³-N⁴). As an integral part of the Center for Predictive Simulation of Functional Materials (CPSFM), we develop efficient algorithms based on AFQMC and massively parallel supercomputer platforms and study transition metal oxides. We control the phase and sign problem with the phaseless formalism. As an example, we calculate the energy and magnetism of NiO in different magnetic states and upon volume changes. Our results agree well with experiments and can benchmark future theoretical investigations.