full name: tenpy.linalg.krylov_based.LanczosGroundState
Find the ground state of H.
- class tenpy.linalg.krylov_based.LanczosGroundState(H, psi0, options, orthogonal_to=)¶
Lanczos algorithm to find the ground state.
Assumes that H is hermitian.
Deprecated since version 0.6.0: Renamed attribute params to
Deprecated since version 0.6.0: Going to remove the orthogonal_to argument. Instead, replace H with
OrthogonalNpcLinearOperator(H, orthogonal_to)using the
- config LanczosGroundState¶
Cutoff to abort if the norm of the new krylov vecotr is too small. [...]
Shift the energy (=eigenvalues) by that amount *during* the Lanczos run by [...]
Stop if energy difference per step < `E_tol`
Lower cutoff for the gap estimate used in the P_tol criterion.
The maximum number of `psi` to keep in memory during the first iteration. [...]
Maximum number of steps to perform.
Minimum number of steps to perform.
Tolerance for the error estimate from the Ritz Residual, [...]
For poorly conditioned matrices, one can quickly loose orthogonality of the [...]
- option E_tol: float¶
Stop if energy difference per step < E_tol
- option N_cache: int¶
The maximum number of psi to keep in memory during the first iteration. By default, we keep all states (up to N_max). Set this to a number >= 2 if you are short on memory. The penalty is that one needs another Lanczos iteration to determine the ground state in the end, i.e., runtime is large.
- option reortho: bool¶
For poorly conditioned matrices, one can quickly loose orthogonality of the generated Krylov basis. If reortho is True, we re-orthogonalize against all the vectors kept in cache to avoid that problem.