Implement spin_op::to_sparse_matrix().

[amccaskey]

Usage:

auto H = 5.907 - 2.1433 * x(0) * x(1) - 2.1433 * y(0) * y(1) + .21829 * z(0) -
         6.125 * z(1);
auto [values, rows, cols] = H.to_sparse_matrix();

hamiltonian = 5.907 - 2.1433 * spin.x(0) * spin.x(1) - 2.1433 * spin.y(
    0) * spin.y(1) + .21829 * spin.z(0) - 6.125 * spin.z(1)
numQubits = hamiltonian.get_qubit_count()
values, rows, cols = hamiltonian.to_sparse_matrix()

# can use scipy 
scipyM = scipy.sparse.csr_array((values, (rows, cols)), shape=(2**numQubits,2**numQubits))
energy, _ = scipy.sparse.linalg.eigsh(scipyM, k=1, which='SA')

[github-actions]

CUDA Quantum Docs Bot: A preview of the documentation can be found here.

[github-actions]

CUDA Quantum Docs Bot: A preview of the documentation can be found here.

[github-actions]

CUDA Quantum Docs Bot: A preview of the documentation can be found here.

[github-actions]

CUDA Quantum Docs Bot: A preview of the documentation can be found here.

[github-actions]

CUDA Quantum Docs Bot: A preview of the documentation can be found here.