bosonic_qiskit.kraus

module documentation

(source)

Undocumented

Class	`PhotonLossNoisePass`	Add photon loss noise model to a circuit during transpiler transformation pass.
Function	`calculate_kraus`	Calculate Kraus operator given number of photons and photon loss rate over specified time.
Constant	`IGNORE_INSTRUCTIONS`	Undocumented
Function	`__kraus_operators`	Calculates the Kraus operators for photon loss
Function	`__tensor_operators`	Undocumented

def calculate_kraus(photon_loss_rates: Sequence[float], time: float, circuit: bosonic_qiskit.CVCircuit, op_qubits: Sequence[int], qumode_qubit_indices: Sequence[int]) -> list[np.ndarray]: (source) ¶

Calculate Kraus operator given number of photons and photon loss rate over specified time.

Apply Kraus operator to provided qubit_indices only, tensor product with identity for remaining qubits.

Following equation 44 from Bosonic Oprations and Measurements, Girvin

Parameters
photon_loss_rates:`Sequence[float]`	kappas, the rate of photon loss per second for each qumode
time:`float`	current duration of time in seconds
circuit:`CVCircuit`	cq2a.CVCircuit with ops for N and a
op_qubits:`Sequence[int]`	qubit int indices in the given CVCircuit used by the current instruction
qumode_qubit_indices:`Sequence[int]`	qumode int indices in the given CVCircuit to test if qubits from instruction are a part of a qumode

Returns
`list[np.ndarray]`	List of Kraus operators

IGNORE_INSTRUCTIONS: list[str] = (source) ¶

Undocumented

Value

['measure']

def __kraus_operators(photon_loss_rate: float, time: float, cutoff: int, a: sp.csc_array, n: sp.csc_array) -> list[np.ndarray]: (source) ¶

Calculates the Kraus operators for photon loss

Parameters
photon_loss_rate:`float`	The rate of photon loss in the qumode
time:`float`	The duration of the noise channel
cutoff:`int`	The maximum fock level of the qumode
a:`sp.csc_array`	The annihilation operator
n:`sp.csc_array`	The photon number operator

Returns
`list[np.ndarray]`	A list of Kraus operators, where operator i corresponds to losing i photons

def __tensor_operators(current: list[np.ndarray], new: list[np.ndarray]) -> list[np.ndarray]: (source) ¶

Undocumented