:py:mod:`state_metrics.bures_distance` ====================================== .. py:module:: state_metrics.bures_distance .. autoapi-nested-parse:: Bures distance metric. Module Contents --------------- Functions ~~~~~~~~~ .. autoapisummary:: state_metrics.bures_distance.bures_distance .. py:function:: bures_distance(rho_1, rho_2, decimals = 10) Compute the Bures distance of two density matrices :cite:`WikiBures`. Calculate the Bures distance between two density matrices :code:`rho_1` and :code:`rho_2` defined by: .. math:: \sqrt{2 (1 - F(\rho_1, \rho_2))}, where :math:`F(\cdot)` denotes the fidelity between :math:`\rho_1` and :math:`\rho_2`. The return is a value between :math:`0` and :math:`\sqrt{2}`,with :math:`0` corresponding to matrices: :code:`rho_1 = rho_2` and :math:`\sqrt{2}` corresponding to the case: :code:`rho_1` and :code:`rho_2` with orthogonal support. .. 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 Bures distance between states that are identical, we should obtain the value of :math:`0`. This can be observed in :code:`toqito` as follows. >>> from toqito.state_metrics import bures_distance >>> 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 >>> bures_distance(rho, sigma) 0.0 .. rubric:: References .. bibliography:: :filter: docname in docnames :raises ValueError: If matrices are not of equal dimension. :param rho_1: Density operator. :param rho_2: Density operator. :param decimals: Number of decimal places to round to (default 10). :return: The Bures distance between :code:`rho_1` and :code:`rho_2`.