Source code for toqito.channels.amplitude_damping
"""Generates the (generalized) amplitude damping channel."""
import numpy as np
[docs]
def amplitude_damping(
input_mat: np.ndarray | None = None,
gamma: float = 0,
prob: float = 1,
) -> np.ndarray | list[np.ndarray]:
r"""Apply the generalized amplitude damping channel to a quantum state.
The generalized amplitude damping channel is a quantum channel that models energy dissipation
in a quantum system, where the system can lose energy to its environment with a certain
probability. This channel is defined by two parameters: `gamma` (the damping rate) and `prob`
(the probability of energy loss).
To also include standard implementation of amplitude damping, we have set `prob = 1` as the default implementation.
!!! note
This channel is defined for qubit systems in the standard literature [@Khatri_2020_Information].
The Kraus operators for the generalized amplitude damping channel are given by:
\[
K_0 = \sqrt{p} \begin{pmatrix} 1 & 0 \\ 0 & \sqrt{1 - \gamma} \end{pmatrix}, \\
K_1 = \sqrt{p} \begin{pmatrix} 0 & \sqrt{\gamma} \\ 0 & 0 \end{pmatrix}, \\
K_2 = \sqrt{1 - p} \begin{pmatrix} \sqrt{1 - \gamma} & 0 \\ 0 & 1 \end{pmatrix}, \\
K_3 = \sqrt{1 - p} \begin{pmatrix} 0 & 0 \\ \sqrt{\gamma} & 0 \end{pmatrix}, \\
\]
These operators describe the evolution of a quantum state under the generalized amplitude
damping process.
Examples:
Apply the generalized amplitude damping channel to a qubit state:
```python exec="1" source="above"
import numpy as np
from toqito.channels import amplitude_damping
rho = np.array([[1, 0], [0, 0]]) # |0><0|
result = amplitude_damping(rho, gamma=0.1, prob=0.5)
print(result)
```
Args:
input_mat: The input matrix to which the channel is applied. If `None`, the function returns the Kraus operators
of the channel.
gamma: The damping rate, a float between 0 and 1. Represents the probability of energy dissipation.
prob: The probability of energy loss, a float between 0 and 1.
Returns:
The evolved quantum state after applying the generalized amplitude damping channel. If `input_mat` is `None`, it
returns the list of Kraus operators.
"""
if not (0 <= prob <= 1):
raise ValueError("Probability must be between 0 and 1.")
if not (0 <= gamma <= 1):
raise ValueError("Gamma (damping rate) must be between 0 and 1.")
k0 = np.sqrt(prob) * np.array([[1, 0], [0, np.sqrt(1 - gamma)]])
k1 = np.sqrt(prob) * np.sqrt(gamma) * np.array([[0, 1], [0, 0]])
k2 = np.sqrt(1 - prob) * np.array([[np.sqrt(1 - gamma), 0], [0, 1]])
k3 = np.sqrt(1 - prob) * np.sqrt(gamma) * np.array([[0, 0], [1, 0]])
if input_mat is not None and input_mat.shape != (2, 2):
raise ValueError("Input matrix must be 2x2 for the generalized amplitude damping channel.")
elif input_mat is None:
return [k0, k1, k2, k3]
input_mat = np.asarray(input_mat, dtype=complex)
return (
k0 @ input_mat @ k0.conj().T
+ k1 @ input_mat @ k1.conj().T
+ k2 @ input_mat @ k2.conj().T
+ k3 @ input_mat @ k3.conj().T
)