John M. Boyer, Charles F. Wiecha
DocEng 2009
Linear-scaling methods have paved the way for large-scale ab initio calculations of solid-state systems. Existing methods suffer from two well-known limitations. First, they are only applicable to sparse systems, i.e., when long-range orbital interactions exponentially decay and therefore the Hamiltonian matrices have a small number of non-zero elements. Second, their computational performance is negatively impacted when high accuracy is needed. In this work, by revisiting linear scaling kernels, we introduce a new approach with nearly-linear complexity, provable convergence properties, and global applicability even for dense systems. We demonstrate their advantages and limitations both in theory and in practice.
John M. Boyer, Charles F. Wiecha
DocEng 2009
Dimitrios Christofidellis, Giorgio Giannone, et al.
ACS Spring 2023
Miruna Cretu, Alessandra Toniato, et al.
ACS Spring 2023
Fan Zhang, Junwei Cao, et al.
IEEE TETC