45 citations · 66 across the 9 of their papers we have counts for
27 papers
Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning
Weile Jia, Han Wang, Mohan Chen +5
For 35 years, {\it ab initio} molecular dynamics (AIMD) has been the method of choice for modeling complex atomistic phenomena from first principles. However, most AIMD application…
Enhancing robustness and efficiency of density matrix embedding theory via semidefinite programming and local correlation potential fitting
Xiaojie Wu, Michael Lindsey, Tiangang Zhou +2
Density matrix embedding theory (DMET) is a powerful quantum embedding method for solving strongly correlated quantum systems. Theoretically, the performance of a quantum embedding…
Split representation of adaptively compressed polarizability operator
Dong An, Lin Lin, Ze Xu
The polarizability operator plays a central role in density functional perturbation theory and other perturbative treatment of first principle electronic structure theories. The co…
Learning the mapping : the cost of finding the needle in a haystack
Jiefu Zhang, Leonardo Zepeda-Núñez, Yuan Yao +1
The task of using machine learning to approximate the mapping with seems to be a trivial one. Given the knowledge of the separa…
Policy Gradient based Quantum Approximate Optimization Algorithm
Jiahao Yao, Marin Bukov, Lin Lin
The quantum approximate optimization algorithm (QAOA), as a hybrid quantum/classical algorithm, has received much interest recently. QAOA can also be viewed as a variational ansatz…
Numerical solution of large scale Hartree-Fock-Bogoliubov equations
Lin Lin, Xiaojie Wu
The Hartree-Fock-Bogoliubov (HFB) theory is the starting point for treating superconducting systems. However, the computational cost for solving large scale HFB equations can be mu…