atlas_q.grover.GroverConfig#

class atlas_q.grover.GroverConfig(n_qubits, oracle_type='function', auto_iterations=True, max_iterations=1000, chi_max=256, device='cuda', dtype=torch.complex128, verbose=False, measure_success_prob=False)[source]#

Bases: object

Configuration for Grover’s algorithm

Attributes:: n_qubits: Number of qubits (search space size = 2^n_qubits) oracle_type: Type of oracle (‘function’, ‘bitmap’, ‘structured’) auto_iterations: Automatically calculate optimal iterations max_iterations: Maximum iterations (safety limit) chi_max: Maximum bond dimension for MPS device: ‘cuda’ or ‘cpu’ dtype: torch.complex64 or torch.complex128 verbose: Print progress information measure_success_prob: Track success probability after each iteration

__init__(n_qubits, oracle_type='function', auto_iterations=True, max_iterations=1000, chi_max=256, device='cuda', dtype=torch.complex128, verbose=False, measure_success_prob=False)#

Methods

__init__(n_qubits[, oracle_type, ...])

Attributes

`auto_iterations`
`chi_max`
`device`
`dtype`
`max_iterations`
`measure_success_prob`
`oracle_type`
`verbose`
`n_qubits`

n_qubits: int#

oracle_type: str = 'function'#

auto_iterations: bool = True#

max_iterations: int = 1000#

chi_max: int = 256#

device: str = 'cuda'#

dtype: dtype = torch.complex128#

verbose: bool = False#

measure_success_prob: bool = False#