Source code for qrisp.qaoa.problems.minSetCover

"""
\********************************************************************************
* Copyright (c) 2024 the Qrisp authors
*
* This program and the accompanying materials are made available under the
* terms of the Eclipse Public License 2.0 which is available at
* http://www.eclipse.org/legal/epl-2.0.
*
* This Source Code may also be made available under the following Secondary
* Licenses when the conditions for such availability set forth in the Eclipse
* Public License, v. 2.0 are satisfied: GNU General Public License, version 2
* with the GNU Classpath Exception which is
* available at https://www.gnu.org/software/classpath/license.html.
*
* SPDX-License-Identifier: EPL-2.0 OR GPL-2.0 WITH Classpath-exception-2.0
********************************************************************************/
"""

from qrisp import QuantumVariable, QuantumBool, x, mcx
from qrisp.algorithms.qaoa.mixers import controlled_RX_mixer_gen


[docs] def create_min_set_cover_mixer(sets, universe): r""" Creates the ``controlled_RX_mixer`` for an instance of the minimum set cover problem following `Hadfield et al. <https://arxiv.org/abs/1709.03489>`_ The belonging ``predicate`` function indicates if a set can be swapped out of the solution. Parameters ---------- sets : list[set] A list of sets. universe : set The union of all sets. Returns ------- function A Python function receiving a ``QuantumVariable`` and real parameter $\beta$. This function performs the application of the mixer associated to the problem instance. """ membership_dict = {element: [i for i, subset in enumerate(sets) if element in subset] for element in universe} def predicate(qv,i): anc = QuantumVariable(len(sets[i])) x(anc) for anc_index, element in enumerate(sets[i]): other_sets = [item for item in membership_dict[element] if item != i] mcx([qv[set_index] for set_index in other_sets],anc[anc_index],ctrl_state="0"*len(other_sets)) qbl = QuantumBool() mcx(anc,qbl) return qbl controlled_RX_mixer=controlled_RX_mixer_gen(predicate) return controlled_RX_mixer
[docs] def create_min_set_cover_cl_cost_function(sets, universe): """ Creates the classical cost function for an instance of the minimum set cover problem. Parameters ---------- sets : list[set] A list of sets. universe : set The union of all sets. Returns ------- cl_cost_function : function The classical cost function for the problem instance, which takes a dictionary of measurement results as input. """ def cl_cost_function(res_dic): cost = 0 for state, prob in res_dic.items(): indices = [index for index, value in enumerate(state) if value == '1'] solution_sets = [sets[index] for index in indices] if len(solution_sets)>0 and set.union(*solution_sets)==universe: cost += len(indices)*prob else: cost += len(sets) return cost return cl_cost_function
[docs] def min_set_cover_init_function(qv): r""" Prepares the initial state $\ket{1}^{\otimes n}$. Parameters ---------- qv : :ref:`QuantumVariable` The quantum argument. """ x(qv)
[docs] def min_set_cover_problem(sets, universe): """ Creates a QAOA problem instance with appropriate phase separator, mixer, and classical cost function. Parameters ---------- sets : list[set] A list of sets. universe : set The union of all sets. Returns ------- :ref:`QAOAProblem` A QAOA problem instance for MinSetCover for given ``sets`` and ``universe``. """ from qrisp.qaoa import QAOAProblem, RZ_mixer return QAOAProblem(cost_operator=RZ_mixer, mixer= create_min_set_cover_mixer(sets, universe), cl_cost_function=create_min_set_cover_cl_cost_function(sets, universe), init_function=min_set_cover_init_function)