:py:mod:`state_metrics.fidelity` ================================ .. py:module:: state_metrics.fidelity .. autoapi-nested-parse:: Fidelity metric. Module Contents --------------- Functions ~~~~~~~~~ .. autoapisummary:: state_metrics.fidelity.fidelity .. py:function:: fidelity(rho, sigma) Compute the fidelity of two density matrices :cite:`WikiFidQuant`. Calculate the fidelity between the two density matrices :code:`rho` and :code:`sigma`, defined by: .. math:: ||\sqrt(\rho) \sqrt(\sigma)||_1, where :math:`|| \cdot ||_1` denotes the trace norm. The return is a value between :math:`0` and :math:`1`, with :math:`0` corresponding to matrices :code:`rho` and :code:`sigma` with orthogonal support, and :math:`1` corresponding to the case :code:`rho = sigma`. .. rubric:: Examples Consider the following Bell state .. math:: u = \frac{1}{\sqrt{2}} \left( |00 \rangle + |11 \rangle \right) \in \mathcal{X}. The corresponding density matrix of :math:`u` may be calculated by: .. math:: \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}). In the event where we calculate the fidelity between states that are identical, we should obtain the value of :math:`1`. This can be observed in :code:`toqito` as follows. >>> from toqito.state_metrics import fidelity >>> import numpy as np >>> rho = 1 / 2 * np.array( ... [[1, 0, 0, 1], ... [0, 0, 0, 0], ... [0, 0, 0, 0], ... [1, 0, 0, 1]] ... ) >>> sigma = rho >>> fidelity(rho, sigma) 1.0000000000000002 .. rubric:: References .. bibliography:: :filter: docname in docnames :raises ValueError: If matrices are not density operators. :param rho: Density operator. :param sigma: Density operator. :return: The fidelity between :code:`rho` and :code:`sigma`.