Quantum many-body calculation methods,including exact diagonalization,quantum Monte Carlo,density matrix and tensor renormalization,and dynamic mean field theory,as well as emerging methods harnessing the power of artificial intelligence and quantum computing,can be used to accurately and efficiently calculate the physical properties of correlated quantum many-body systems.The quantum particles in the interacting,non-perturbative many-body system are highly entangled,and the mean field theory often lacks sufficient accuracy or may even break down for certain problems.It is thus very necessary to develop new methods for studying the exotic states and emergent phenomena in correlated systems,such as high-temperature superconductivity and frustrated quantum magnetism.Recently,the rapid progress in the field of many-body calculation has shown the characteristics of interdisciplinary cross,and there is increasingly significant interplay and integration with machine learning,materials science,quantum simulation and computation,among other fields.This paper outlines the brief history of many-body calculations,major approaches and their current status,as well as main challenges in this field.
关键词
多体计算/精确对角化/蒙特卡罗方法/张量网络/动力学平均场/机器学习/量子计算与量子模拟
Key words
many-body calculation/exact diagonalization/Monte Carlo method/tensor network/dynamic mean field theory/machine learning/quantum computation and simulation
维普
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