supermarq.benchmarks.qaoa_fermionic_swap_proxy
==============================================

.. py:module:: supermarq.benchmarks.qaoa_fermionic_swap_proxy

.. autoapi-nested-parse::

   Definition of the Fermionic SWAP QAOA benchmark within the Supermarq suite.



Classes
-------

.. autoapisummary::

   supermarq.benchmarks.qaoa_fermionic_swap_proxy.QAOAFermionicSwapProxy


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

.. py:class:: QAOAFermionicSwapProxy(num_qubits: int)

   Bases: :py:obj:`supermarq.benchmarks.qaoa_vanilla_proxy.QAOAVanillaProxy`


   Proxy of a full Quantum Approximate Optimization Algorithm (QAOA) benchmark.

   This benchmark targets MaxCut on a Sherrington-Kirkpatrick (SK) model. Device
   performance is given by the Hellinger fidelity between the experimental output
   distribution and the true distribution obtained via scalable, classical simulation.

   The ansatz for this QAOA problem utilizes the fermionic SWAP network which is able
   to perform all of the required O(N^2) interactions in linear circuit depth. This
   ansatz is especially well-suited to QPU architectures which only support
   nearest-neighbor connectivity. See https://doi.org/10.3390/electronics10141690 for
   an example of this ansatz used in practice.

   When a new instance of this benchmark is created, the ansatz parameters will
   be initialized by:

   #. Generating a random instance of an SK graph

   #. Finding approximately optimal angles (rather than random values)