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:
HUnion[MPO, MPOList, MPOSum]

Hamiltonian in MPO form.

guessOptional[MPS]

Initial guess of the ground state. If None, defaults to a random MPS deduced from the operator’s dimensions.

maxiterint

Maximum number of iterations (defaults to 1000).

nvectors: int

Number of vectors in the Krylov basis (defaults to 10).

tolfloat

Energy variation that indicates termination (defaults to 1e-13).

tol_upfloat, default = tol

If energy fluctuates up below this tolerance, continue the optimization.

tol_illfloat

Check for ill conditioning of the Krylov basis (defaults to 1e-15).

gammafloat

If nonzero, convergence acceleration factor. Default is 0.0 (no inertia). Alternatively, provide -0.75.

strategyOptional[Strategy]

Linear combination of MPS truncation strategy. Defaults to DESCENT_STRATEGY.

callbackOptional[Callable[[MPS, OptimizeResults], Any]]

A callable called after each iteration (defaults to None).