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 )