Releases: lanczos-iterator/Lanczos_Iterator
Lanczos_Iterator v3.3.2
This is an iterative Lanczos procedure (Fortran 95 with C99 interface) for maximum-accuracy eigenvectors and eigenvalues of (complex or real) Hermitian matrices specified as a "black box" matrix-vector multiplication procedure (MATVEC) implemented in 64-bit floating-point arithmetic. The maximum possible accuracy of its eigenvalues is determined, and residual norms of eigenvectors are polished down to this scale; eigenvector degeneracies are fully resolved. Suitable for matrix dimensions up to tens of millions, or more, for which an efficient MATVEC is available.
- This procedure will be of interest to condensed-matter theorists working on interacting quantum many-body problems using exact-diagonalization methods.
Changelog:
some cosmetic fixes, plus double matvec option
(M-> (M-E)*(M-E) for possible interior eigenvalue/vector use.
Lanczos_Iterator v3.3.1
This is an iterative Lanczos procedure (Fortran 95 with C99 interface) for maximum-accuracy eigenvectors and eigenvalues of (complex or real) Hermitian matrices specified as a "black box" matrix-vector multiplication procedure (MATVEC) implemented in 64-bit floating-point arithmetic. The maximum possible accuracy of its eigenvalues is determined, and residual norms of eigenvectors are polished down to this scale; eigenvector degeneracies are fully resolved. Suitable for matrix dimensions up to tens of millions, or more, for which an efficient MATVEC is available.
This procedure will be of interest to condensed-matter theorists working on interacting quantum many-body problems using exact-diagonalization methods.
Changelog:
remove use of 1/huge in tmatrix_m
Lanczos_Iterator-v3.3
This is an iterative Lanczos procedure (Fortran 95 with C99 interface) for maximum-accuracy eigenvectors and eigenvalues of (complex or real) Hermitian matrices specified as a "black box" matrix-vector multiplication procedure (MATVEC) implemented in 64-bit floating-point arithmetic. The maximum possible accuracy of its eigenvalues is determined, and residual norms of eigenvectors are polished down to this scale; eigenvector degeneracies are fully resolved. Suitable for matrix dimensions up to tens of millions, or more, for which an efficient MATVEC is available.
- This procedure will be of interest to condensed-matter theorists working on interacting quantum many-body problems using exact-diagonalization methods.