supermarq.benchmarks.ghz
========================

.. py:module:: supermarq.benchmarks.ghz


Classes
-------

.. autoapisummary::

   supermarq.benchmarks.ghz.GHZ


Module Contents
---------------

.. py:class:: GHZ(num_qubits: int, method: str = 'ladder')

   Bases: :py:obj:`supermarq.benchmark.Benchmark`


   Represents the GHZ state preparation benchmark parameterized by the number of qubits n.

   Device performance is based on the Hellinger fidelity between the experimental and ideal
   probability distributions.


   .. py:method:: circuit() -> cirq.Circuit

      Generate an n-qubit GHZ cirq circuit.

      :returns: A `cirq.Circuit`.



   .. py:method:: qiskit_circuit() -> qiskit.QuantumCircuit

      Generate an n-qubit GHZ qiskit circuit.

      :returns: A `qiskit.QuantumCircuit`.



   .. py:method:: score(counts: dict[str, float]) -> float

      Compute the Hellinger fidelity between the experimental and ideal results.

      The ideal results are 50% probabilty of measuring the all-zero state and 50% probability
      of measuring the all-one state.

      The formula for the Hellinger fidelity between two distributions p and q is given by
      $(\sum_i{p_i q_i})^2$.

      :param counts: A dictionary containing the measurement counts from circuit execution.

      :returns: Hellinger fidelity as a float.



   .. py:attribute:: method
      :value: 'ladder'



   .. py:attribute:: num_qubits