Merge branch 'master' of https://github.com/ornl-qci/qcor

// In this demo, we use a built-in QAOA ansatz circuit

// with QCOR's VQE Objective Function.

// Note: we can also explicitly construct this ansatz circuit in QCOR.

// e.g., see qaoa_example.cpp

#include <qalloc>

#include "qcor.hpp"

__qpu__ void qaoa_ansatz(qreg q, int n, std::vector<double> betas, std::vector<double> gammas, qcor::PauliOperator& costHamiltonian, qcor::PauliOperator& refHamiltonian) {

  // Just use the built-in qaoa circuit

  qaoa(q, n, betas, gammas, costHamiltonian, refHamiltonian);

}

// Compile (using Qpp simulator backend)

// qcor -o qaoa-example -qpu qpp qaoa-builtin-circuit.cpp

int main(int argc, char **argv) {

  auto buffer = qalloc(2);

  auto optimizer = qcor::createOptimizer("nlopt");

  // Cost Hamiltonian

  auto observable = 5.907-2.1433*qcor::X(0)*qcor::X(1)-2.1433*qcor::Y(0)*qcor::Y(1)+0.21829*qcor::Z(0)-6.125*qcor::Z(1);

  // Mixer Hamiltonian

  auto refHamiltonian = qcor::X(0) + qcor::X(1);

  // VQE objective function

  auto vqe = qcor::createObjectiveFunction("vqe", qaoa_ansatz, observable);

  vqe->set_qreg(buffer);

  // QAOA variational parameters

  const int nbSteps = 2;

  const int nbParamsPerStep = 2 /*beta (mixer)*/ + 4 /*gamma (cost)*/;

  const int totalParams = nbSteps * nbParamsPerStep;

  int iterCount = 0;

  // Optimization function

  qcor::OptFunction f(

      [&](const std::vector<double> x, std::vector<double> &grad) {

        std::vector<double> betas;

        std::vector<double> gammas;

        // Unpack nlopt params

        // Beta: nbSteps * number qubits

        for (int i = 0; i < nbSteps * buffer.size(); ++i) {

          betas.emplace_back(x[i]);

        }

        for (int i = betas.size(); i < x.size(); ++i) {

          gammas.emplace_back(x[i]);

        }

        // Evaluate the objective function

        const double costVal = (*vqe)(buffer, buffer.size(), betas, gammas, observable, refHamiltonian);

        std::cout << "Iter " << iterCount << ": Cost = " << costVal << "\n";

        iterCount++;

        return costVal;

      },

      totalParams);

  auto results = optimizer->optimize(f);

  std::cout << "Final cost: " << results.first << "\n";

}