seemps.optimization.arnoldi.arnoldi_eigh#
- seemps.optimization.arnoldi.arnoldi_eigh(operator, guess=None, maxiter=100, nvectors=10, tol=1e-13, tol_ill=np.float64(2.220446049250313e-15), tol_up=None, upward_moves=5, gamma=-0.75, strategy=<seemps.state.core.Strategy object>, callback=None)[source]#
Ground state search of Hamiltonian H by the Arnoldi method.
- Parameters:
- H
Union
[MPO
,MPOList
,MPOSum
] Hamiltonian in MPO form.
- guess
Optional
[MPS
] Initial guess of the ground state. If None, defaults to a random MPS deduced from the operator’s dimensions.
- maxiter
int
Maximum number of iterations (defaults to 1000).
- nvectors: int
Number of vectors in the Krylov basis (defaults to 10).
- tol
float
Energy variation that indicates termination (defaults to 1e-13).
- tol_up
float
,default
= tol If energy fluctuates up below this tolerance, continue the optimization.
- tol_ill
float
Check for ill conditioning of the Krylov basis (defaults to 1e-15).
- gamma
float
If nonzero, convergence acceleration factor. Default is 0.0 (no inertia). Alternatively, provide -0.75.
- strategy
Optional
[Strategy
] Linear combination of MPS truncation strategy. Defaults to DESCENT_STRATEGY.
- callback
Optional
[Callable
[[MPS
,OptimizeResults
],Any
]] A callable called after each iteration (defaults to None).
- H