vibeqc.DMRGOptions

class vibeqc.DMRGOptions(target_size=100, conv_tol_energy=1e-06, max_iter=50, verbose=0, random_seed=42, bond_dim=64, bond_dim_schedule=<factory>, n_sweeps=10, n_lanczos_iter=20, truncation_tol=1e-08, orbital_order=None, noise=0.0)

Bases: SolverOptions

Options for the DMRG solver.

Parameters:

• target_size (int)

• conv_tol_energy (float)

• max_iter (int)

• verbose (int)

• random_seed (int)

• bond_dim (int)

• bond_dim_schedule (list[int])

• n_sweeps (int)

• n_lanczos_iter (int)

• truncation_tol (float)

• orbital_order (list[int] | None)

• noise (float)

__init__(target_size=100, conv_tol_energy=1e-06, max_iter=50, verbose=0, random_seed=42, bond_dim=64, bond_dim_schedule=<factory>, n_sweeps=10, n_lanczos_iter=20, truncation_tol=1e-08, orbital_order=None, noise=0.0)

Parameters:

• target_size (int)

• conv_tol_energy (float)

• max_iter (int)

• verbose (int)

• random_seed (int)

• bond_dim (int)

• bond_dim_schedule (list[int])

• n_sweeps (int)

• n_lanczos_iter (int)

• truncation_tol (float)

• orbital_order (list[int] | None)

• noise (float)

Return type:

None

Methods

__init__([target_size, conv_tol_energy, ...])

Attributes

bond_dim
conv_tol_energy	Energy convergence threshold (Hartree).
max_iter	Maximum number of macro-iterations.
n_lanczos_iter
n_sweeps
noise
orbital_order
random_seed	Random seed for reproducibility.
target_size	Target number of determinants / bond-dimension / constraint set size.
truncation_tol
verbose	0 = silent, 1 = per-iteration, 2 = debug.
bond_dim_schedule

bond_dim: int = 64

bond_dim_schedule: list[int]

n_sweeps: int = 10

n_lanczos_iter: int = 20

truncation_tol: float = 1e-08

orbital_order: list[int] | None = None

noise: float = 0.0