quairkit.ansatz.comb¶

The source file of the PQCombNet class.

class quairkit.ansatz.comb.PQCombNet(target_function, num_slots, num_aux_qubits, num_qubits_U=1, train_unitary_info=200, test_unitary_info=1000, train_mode='choi', LR=0.1, NUM_ITR=1000, name_task=None, seed=None, is_save_data=False, is_auto_stop=True, is_ctrl_U=False)¶

Parameterized Quantum Comb Net.

Parameters:¶

target_function : Callable[[Tensor], Tensor]¶

The function to apply to each tensor in the dataset.

num_slots : int¶

The parameter ‘num_slots’ used in the specific quantum computation context.

num_aux_qubits : int¶

The parameter ‘num_aux_qubits’ also used in the quantum computation context.

num_qubits_U : int¶

The number of qubits of the unitaries to be queried.

train_unitary_info : int | Tensor¶

Information for generating or providing training unitaries, either as an integer or a tensor.

test_unitary_info : int | Tensor¶

Information for generating or providing testing unitaries, similar to train_unitary_info.

train_mode : str¶

The mode to use for training, default is ‘choi’.

LR : float¶

Learning rate for the optimization algorithm.

NUM_ITR : int¶

Number of iterations to run the training.

name_task : str¶

Optional name for the task, useful for data logging and storage.

seed : int | None¶

Optional seed for random number generation, enhancing reproducibility.

is_save_data : bool¶

Flag to determine if data should be saved during training.

is_auto_stop : bool¶

Flag to enable stopping the training process automatically based on certain criteria.

is_ctrl_U : bool¶

Flag to indicate if a controlled-U operation is used in the training process.

update_V_circuit(index, new_V)¶

Update the V circuit at the specified index with a new circuit.

Parameters:¶

index : int¶

The index of the V circuit to update.

new_V : Circuit | ParamOracle | Tensor | Tuple[Tensor, List[int]]¶

The new V circuit, which can be a ParamOracle, Circuit, torch.Tensor or Tuple[torch.Tensor, List[int]].

Raises:¶

• ValueError – If the index is out of range or if the number of qubits in the provided Circuit does not match the number of qubits in the existing Circuit.

• TypeError – If new_V is not a ParamOracle, Circuit, torch.Tensor or Tuple[torch.Tensor, List[int]].

train()¶

Train the PQCombNet model.

extract_highest_fidelity()¶

Call the _extract_highest_fidelity function to generate the fidelity tables. If the file does not exist, prompt the user to set is_save_data to True.