2000/02/29 by Dean Lee, Nathan Salwen, Daniel Lee · 44 citations
Chemistry · Mathematics · Physics and Astronomy · #Advanced Chemical Physics Studies #Advanced NMR Techniques and Applications #Basis (linear algebra) #Diagonalizable matrix #Eigenvalues and eigenvectors #Hamiltonian (control theory) #Hermitian matrix #Mathematical optimization #Mathematics #Monte Carlo method #Physics #Quantum #Quantum Monte Carlo #Quantum and electron transport phenomena #Quantum mechanics #Statistical physics #Symmetric matrix #cond-mat #hep-lat #hep-ph #hep-th #nucl-th #quant-ph
paper · pdf · doi:10.1016/s0370-2693(01)00197-6
published in Physics Letters B 503(1-2), 223-235 (Elsevier BV) · 12 pages, 8 figures, new material added
arxiv created 2000/10/24 · openalex publication_date 2001/03/01 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We introduce a new diagonalization method called quasi-sparse eigenvector diagonalization which finds the most important basis vectors of the low energy eigenstates of a quantum Hamiltonian. It can operate using any basis, either orthogonal or non-orthogonal, and any sparse Hamiltonian, either Hermitian, non-Hermitian, finite-dimensional, or infinite-dimensional. The method is part of a new computational approach which combines both diagonalization and Monte Carlo techniques.