Source code for toqito.state_props.is_pure

"""Checks if a quantum state is a pure state."""

import numpy as np


[docs] def is_pure(state: list[np.ndarray] | np.ndarray) -> bool: r"""Determine if a given state is pure or list of states are pure [@WikiPureSt]. A state is said to be pure if it is a density matrix with rank equal to 1. Equivalently, the state \(\rho\) is pure if there exists a unit vector \(u\) such that: \[ \rho = u u^*. \] Examples: Consider the following Bell state: \[ u = \frac{1}{\sqrt{2}} \left( |00 \rangle + |11 \rangle \right) \in \mathcal{X}. \] The corresponding density matrix of \(u\) may be calculated by: \[ \rho = u u^* = \frac{1}{2} \begin{pmatrix} 1 & 0 & 0 & 1 \\ 0 & 0 & 0 & 0 \\ 0 & 0 & 0 & 0 \\ 1 & 0 & 0 & 1 \end{pmatrix} \in \text{D}(\mathcal{X}). \] Calculating the rank of \(\rho\) yields that the \(\rho\) is a pure state. This can be confirmed in `|toqito⟩` as follows: ```python exec="1" source="above" from toqito.states import bell from toqito.state_props import is_pure u = bell(0) rho = u @ u.conj().T print(is_pure(rho)) ``` It is also possible to determine whether a set of density matrices are pure. For instance, we can see that the density matrices corresponding to the four Bell states yield a result of `True` indicating that all states provided to the function are pure. ```python exec="1" source="above" from toqito.states import bell from toqito.state_props import is_pure u0, u1, u2, u3 = bell(0), bell(1), bell(2), bell(3) rho0 = u0 @ u0.conj().T rho1 = u1 @ u1.conj().T rho2 = u2 @ u2.conj().T rho3 = u3 @ u3.conj().T print(is_pure([rho0, rho1, rho2, rho3])) ``` Args: state: The density matrix representing the quantum state or a list of density matrices representing quantum states. Returns: `True` if state is pure and `False` otherwise. """ # Allow the user to enter a list of states to check. if isinstance(state, list): for rho in state: eigs, _ = np.linalg.eig(rho) if not np.allclose(np.max(np.diag(eigs)), 1): return False return True # Otherwise, if the user just put in a single state, check that. eigs, _ = np.linalg.eig(state) return np.allclose(np.max(np.diag(eigs)), 1)