def test_model_integration_with_constant(self):
# Compute Hamiltonian in both momentum and position space.
length_scale = 0.7
grid = Grid(dimensions=2, length=3, scale=length_scale)
spinless = True
# Include the Madelung constant in the momentum but not the position
# Hamiltonian.
momentum_hamiltonian = jellium_model(grid,
spinless,
True,
include_constant=True)
position_hamiltonian = jellium_model(grid, spinless, False)
# Diagonalize and confirm the same energy.
jw_momentum = jordan_wigner(momentum_hamiltonian)
jw_position = jordan_wigner(position_hamiltonian)
momentum_spectrum = eigenspectrum(jw_momentum)
position_spectrum = eigenspectrum(jw_position)
# Confirm momentum spectrum is shifted 2.8372 / length_scale higher.
max_difference = numpy.amax(momentum_spectrum - position_spectrum)
min_difference = numpy.amax(momentum_spectrum - position_spectrum)
self.assertAlmostEqual(max_difference, 2.8372 / length_scale)
self.assertAlmostEqual(min_difference, 2.8372 / length_scale)
def test_bk_jw_majoranas(self):
# Check if the Majorana operators have the same spectrum
# irrespectively of the transform.
n_qubits = 7
a = FermionOperator(((1, 0), ))
a_dag = FermionOperator(((1, 1), ))
c = a + a_dag
d = 1j * (a_dag - a)
c_spins = [jordan_wigner(c), bravyi_kitaev(c)]
d_spins = [jordan_wigner(d), bravyi_kitaev(d)]
c_sparse = [
get_sparse_operator(c_spins[0]),
get_sparse_operator(c_spins[1])
]
d_sparse = [
get_sparse_operator(d_spins[0]),
get_sparse_operator(d_spins[1])
]
c_spectrum = [eigenspectrum(c_spins[0]), eigenspectrum(c_spins[1])]
d_spectrum = [eigenspectrum(d_spins[0]), eigenspectrum(d_spins[1])]
self.assertAlmostEqual(
0., numpy.amax(numpy.absolute(d_spectrum[0] - d_spectrum[1])))
def get_interaction_rdm(qubit_operator, n_qubits=None):
"""Build an InteractionRDM from measured qubit operators.
Returns: An InteractionRDM object.
"""
# Avoid circular import.
from fermilib.transforms import jordan_wigner
if n_qubits is None:
n_qubits = count_qubits(qubit_operator)
one_rdm = numpy.zeros((n_qubits, ) * 2, dtype=complex)
two_rdm = numpy.zeros((n_qubits, ) * 4, dtype=complex)
# One-RDM.
for i, j in itertools.product(range(n_qubits), repeat=2):
transformed_operator = jordan_wigner(FermionOperator(((i, 1), (j, 0))))
for term, coefficient in iteritems(transformed_operator.terms):
if term in qubit_operator.terms:
one_rdm[i, j] += coefficient * qubit_operator.terms[term]
# Two-RDM.
for i, j, k, l in itertools.product(range(n_qubits), repeat=4):
transformed_operator = jordan_wigner(
FermionOperator(((i, 1), (j, 1), (k, 0), (l, 0))))
for term, coefficient in iteritems(transformed_operator.terms):
if term in qubit_operator.terms:
two_rdm[i, j, k, l] += coefficient * qubit_operator.terms[term]
return InteractionRDM(one_rdm, two_rdm)
def test_plane_wave_hamiltonian_integration(self):
length_set = [3, 4]
spinless_set = [True, False]
geometry = [('H', (0, )), ('H', (0.8, ))]
length_scale = 1.1
for l in length_set:
for spinless in spinless_set:
grid = Grid(dimensions=1, scale=length_scale, length=l)
h_plane_wave = plane_wave_hamiltonian(grid,
geometry,
spinless,
True,
include_constant=True)
h_dual_basis = plane_wave_hamiltonian(grid, geometry, spinless,
False)
jw_h_plane_wave = jordan_wigner(h_plane_wave)
jw_h_dual_basis = jordan_wigner(h_dual_basis)
h_plane_wave_spectrum = eigenspectrum(jw_h_plane_wave)
h_dual_basis_spectrum = eigenspectrum(jw_h_dual_basis)
max_diff = numpy.amax(h_plane_wave_spectrum -
h_dual_basis_spectrum)
min_diff = numpy.amin(h_plane_wave_spectrum -
h_dual_basis_spectrum)
self.assertAlmostEqual(max_diff, 2.8372 / length_scale)
self.assertAlmostEqual(min_diff, 2.8372 / length_scale)
def test_identity(self):
n_qubits = 5
transmed_i = reverse_jordan_wigner(self.identity, n_qubits)
expected_i = FermionOperator(())
self.assertTrue(transmed_i.isclose(expected_i))
retransmed_i = jordan_wigner(transmed_i)
self.assertTrue(self.identity.isclose(retransmed_i))
def test_jordan_wigner_position_jellium(self):
# Parameters.
n_dimensions = 2
grid_length = 3
length_scale = 1.
spinless = 1
# Compute fermionic Hamiltonian.
fermion_hamiltonian = jellium_model(
n_dimensions, grid_length, length_scale, spinless, 0)
qubit_hamiltonian = jordan_wigner(fermion_hamiltonian)
# Compute Jordan-Wigner Hamiltonian.
test_hamiltonian = jordan_wigner_position_jellium(
n_dimensions, grid_length, length_scale, spinless)
# Make sure Hamiltonians are the same.
self.assertTrue(test_hamiltonian.isclose(qubit_hamiltonian))
# Check number of terms.
n_qubits = count_qubits(qubit_hamiltonian)
if spinless:
paper_n_terms = 1 - .5 * n_qubits + 1.5 * (n_qubits ** 2)
else:
paper_n_terms = 1 - .5 * n_qubits + n_qubits ** 2
num_nonzeros = sum(1 for coeff in qubit_hamiltonian.terms.values() if
coeff != 0.0)
self.assertTrue(num_nonzeros <= paper_n_terms)
def test_jordan_wigner_dual_basis_jellium(self):
# Parameters.
grid = Grid(dimensions=2, length=3, scale=1.)
spinless = True
# Compute fermionic Hamiltonian. Include then subtract constant.
fermion_hamiltonian = dual_basis_jellium_model(grid,
spinless,
include_constant=True)
qubit_hamiltonian = jordan_wigner(fermion_hamiltonian)
qubit_hamiltonian -= QubitOperator((), 2.8372)
# Compute Jordan-Wigner Hamiltonian.
test_hamiltonian = jordan_wigner_dual_basis_jellium(grid, spinless)
# Make sure Hamiltonians are the same.
self.assertTrue(test_hamiltonian.isclose(qubit_hamiltonian))
# Check number of terms.
n_qubits = count_qubits(qubit_hamiltonian)
if spinless:
paper_n_terms = 1 - .5 * n_qubits + 1.5 * (n_qubits**2)
num_nonzeros = sum(1 for coeff in qubit_hamiltonian.terms.values()
if coeff != 0.0)
self.assertTrue(num_nonzeros <= paper_n_terms)
def setUp(self):
self.n_qubits = 5
self.fermion_term = FermionOperator('1^ 2^ 3 4', -3.17)
self.fermion_operator = self.fermion_term + hermitian_conjugated(
self.fermion_term)
self.qubit_operator = jordan_wigner(self.fermion_operator)
self.interaction_operator = get_interaction_operator(
self.fermion_operator)
def test_zero(self):
n_qubits = 5
transmed_i = reverse_jordan_wigner(QubitOperator(), n_qubits)
expected_i = FermionOperator()
self.assertTrue(transmed_i.isclose(expected_i))
retransmed_i = jordan_wigner(transmed_i)
self.assertTrue(expected_i.isclose(retransmed_i))
def test_model_integration(self):
# Compute Hamiltonian in both momentum and position space.
grid = Grid(dimensions=2, length=3, scale=1.0)
spinless = True
momentum_hamiltonian = jellium_model(grid, spinless, True)
position_hamiltonian = jellium_model(grid, spinless, False)
# Diagonalize and confirm the same energy.
jw_momentum = jordan_wigner(momentum_hamiltonian)
jw_position = jordan_wigner(position_hamiltonian)
momentum_spectrum = eigenspectrum(jw_momentum)
position_spectrum = eigenspectrum(jw_position)
# Confirm spectra are the same.
difference = numpy.amax(
numpy.absolute(momentum_spectrum - position_spectrum))
self.assertAlmostEqual(difference, 0.)
def test_potential_integration(self):
# Compute potential energy operator in momentum and position space.
grid = Grid(dimensions=2, length=3, scale=2.)
spinless = 1
momentum_potential = plane_wave_potential(grid, spinless)
position_potential = dual_basis_potential(grid, spinless)
# Diagonalize and confirm the same energy.
jw_momentum = jordan_wigner(momentum_potential)
jw_position = jordan_wigner(position_potential)
momentum_spectrum = eigenspectrum(jw_momentum)
position_spectrum = eigenspectrum(jw_position)
# Confirm spectra are the same.
difference = numpy.amax(
numpy.absolute(momentum_spectrum - position_spectrum))
self.assertAlmostEqual(difference, 0.)
def test_kinetic_integration(self):
# Compute kinetic energy operator in both momentum and position space.
grid = Grid(dimensions=2, length=2, scale=3.)
spinless = False
momentum_kinetic = plane_wave_kinetic(grid, spinless)
position_kinetic = dual_basis_kinetic(grid, spinless)
# Diagonalize and confirm the same energy.
jw_momentum = jordan_wigner(momentum_kinetic)
jw_position = jordan_wigner(position_kinetic)
momentum_spectrum = eigenspectrum(jw_momentum)
position_spectrum = eigenspectrum(jw_position)
# Confirm spectra are the same.
difference = numpy.amax(
numpy.absolute(momentum_spectrum - position_spectrum))
self.assertAlmostEqual(difference, 0.)
def test_get_qubit_expectations(self):
qubit_operator = jordan_wigner(self.hamiltonian)
qubit_expectations = self.rdm.get_qubit_expectations(qubit_operator)
test_energy = qubit_operator.terms[()]
for qubit_term in qubit_expectations.terms:
term_coefficient = qubit_operator.terms[qubit_term]
test_energy += (term_coefficient *
qubit_expectations.terms[qubit_term])
self.assertLess(abs(test_energy - self.cisd_energy), EQ_TOLERANCE)
def test_z(self):
pauli_z = QubitOperator(((2, 'Z'), ))
transmed_z = reverse_jordan_wigner(pauli_z)
expected = (FermionOperator(()) + FermionOperator(
((2, 1), (2, 0)), -2.))
self.assertTrue(transmed_z.isclose(expected))
retransmed_z = jordan_wigner(transmed_z)
self.assertTrue(pauli_z.isclose(retransmed_z))
def test_xy(self):
xy = QubitOperator(((4, 'X'), (5, 'Y')), -2.j)
transmed_xy = reverse_jordan_wigner(xy)
retransmed_xy = jordan_wigner(transmed_xy)
expected1 = -2j * (FermionOperator(((4, 1), ), 1j) - FermionOperator(
((4, 0), ), 1j))
expected2 = (FermionOperator(((5, 1), )) - FermionOperator(((5, 0), )))
expected = expected1 * expected2
self.assertTrue(xy.isclose(retransmed_xy))
self.assertTrue(
normal_ordered(transmed_xy).isclose(normal_ordered(expected)))
def test_bk_jw_number_operator(self):
# Check if number operator has the same spectrum in both
# BK and JW representations
n = number_operator(1, 0)
jw_n = jordan_wigner(n)
bk_n = bravyi_kitaev(n)
# Diagonalize and make sure the spectra are the same.
jw_spectrum = eigenspectrum(jw_n)
bk_spectrum = eigenspectrum(bk_n)
self.assertAlmostEqual(
0., numpy.amax(numpy.absolute(jw_spectrum - bk_spectrum)))
def test_yy(self):
yy = QubitOperator(((2, 'Y'), (3, 'Y')), 2.)
transmed_yy = reverse_jordan_wigner(yy)
retransmed_yy = jordan_wigner(transmed_yy)
expected1 = -(FermionOperator(((2, 1), ), 2.) + FermionOperator(
((2, 0), ), 2.))
expected2 = (FermionOperator(((3, 1), )) - FermionOperator(((3, 0), )))
expected = expected1 * expected2
self.assertTrue(yy.isclose(retransmed_yy))
self.assertTrue(
normal_ordered(transmed_yy).isclose(normal_ordered(expected)))
def test_kinetic_integration(self):
# Compute kinetic energy operator in both momentum and position space.
n_dimensions = 2
grid_length = 2
length_scale = 3.
spinless = 0
momentum_kinetic = momentum_kinetic_operator(
n_dimensions, grid_length, length_scale, spinless)
position_kinetic = position_kinetic_operator(
n_dimensions, grid_length, length_scale, spinless)
# Diagonalize and confirm the same energy.
jw_momentum = jordan_wigner(momentum_kinetic)
jw_position = jordan_wigner(position_kinetic)
momentum_spectrum = eigenspectrum(jw_momentum)
position_spectrum = eigenspectrum(jw_position)
# Confirm spectra are the same.
difference = numpy.amax(
numpy.absolute(momentum_spectrum - position_spectrum))
self.assertAlmostEqual(difference, 0.)
def test_model_integration(self):
# Compute Hamiltonian in both momentum and position space.
n_dimensions = 2
grid_length = 3
length_scale = 1.
spinless = 1
momentum_hamiltonian = jellium_model(
n_dimensions, grid_length, length_scale, spinless, 1)
position_hamiltonian = jellium_model(
n_dimensions, grid_length, length_scale, spinless, 0)
# Diagonalize and confirm the same energy.
jw_momentum = jordan_wigner(momentum_hamiltonian)
jw_position = jordan_wigner(position_hamiltonian)
momentum_spectrum = eigenspectrum(jw_momentum)
position_spectrum = eigenspectrum(jw_position)
# Confirm spectra are the same.
difference = numpy.amax(
numpy.absolute(momentum_spectrum - position_spectrum))
self.assertAlmostEqual(difference, 0.)
def test_bk_jw_number_operator_scaled(self):
# Check if number operator has the same spectrum in both
# JW and BK representations
n_qubits = 1
n = number_operator(n_qubits, 0, coefficient=2) # eigenspectrum (0,2)
jw_n = jordan_wigner(n)
bk_n = bravyi_kitaev(n)
# Diagonalize and make sure the spectra are the same.
jw_spectrum = eigenspectrum(jw_n)
bk_spectrum = eigenspectrum(bk_n)
self.assertAlmostEqual(
0., numpy.amax(numpy.absolute(jw_spectrum - bk_spectrum)))
def test_bk_jw_hopping_operator(self):
# Check if the spectrum fits for a single hoppping operator
n_qubits = 5
ho = FermionOperator(((1, 1), (4, 0))) + FermionOperator(
((4, 1), (1, 0)))
jw_ho = jordan_wigner(ho)
bk_ho = bravyi_kitaev(ho)
# Diagonalize and make sure the spectra are the same.
jw_spectrum = eigenspectrum(jw_ho)
bk_spectrum = eigenspectrum(bk_ho)
self.assertAlmostEqual(
0., numpy.amax(numpy.absolute(jw_spectrum - bk_spectrum)))
def test_xx(self):
xx = QubitOperator(((3, 'X'), (4, 'X')), 2.)
transmed_xx = reverse_jordan_wigner(xx)
retransmed_xx = jordan_wigner(transmed_xx)
expected1 = (FermionOperator(((3, 1), ), 2.) - FermionOperator(
((3, 0), ), 2.))
expected2 = (FermionOperator(((4, 1), ), 1.) + FermionOperator(
((4, 0), ), 1.))
expected = expected1 * expected2
self.assertTrue(xx.isclose(retransmed_xx))
self.assertTrue(
normal_ordered(transmed_xx).isclose(normal_ordered(expected)))
def test_yx(self):
yx = QubitOperator(((0, 'Y'), (1, 'X')), -0.5)
transmed_yx = reverse_jordan_wigner(yx)
retransmed_yx = jordan_wigner(transmed_yx)
expected1 = 1j * (FermionOperator(((0, 1), )) + FermionOperator(
((0, 0), )))
expected2 = -0.5 * (FermionOperator(((1, 1), )) + FermionOperator(
((1, 0), )))
expected = expected1 * expected2
self.assertTrue(yx.isclose(retransmed_yx))
self.assertTrue(
normal_ordered(transmed_yx).isclose(normal_ordered(expected)))
def test_u_operator_integration(self):
n_dimensions = 1
length_scale = 1
grid_length = 3
spinless_set = [True, False]
nuclear_charges = numpy.empty((3))
nuclear_charges[0] = 1
nuclear_charges[1] = -3
nuclear_charges[2] = 2
for spinless in spinless_set:
u_plane_wave = plane_wave_u_operator(
n_dimensions, grid_length, length_scale, nuclear_charges,
spinless)
u_dual_basis = dual_basis_u_operator(
n_dimensions, grid_length, length_scale, nuclear_charges,
spinless)
jw_u_plane_wave = jordan_wigner(u_plane_wave)
jw_u_dual_basis = jordan_wigner(u_dual_basis)
u_plane_wave_spectrum = eigenspectrum(jw_u_plane_wave)
u_dual_basis_spectrum = eigenspectrum(jw_u_dual_basis)
diff = numpy.amax(numpy.absolute(
u_plane_wave_spectrum - u_dual_basis_spectrum))
self.assertAlmostEqual(diff, 0)
def test_jordan_wigner_dual_basis_hamiltonian(self):
grid = Grid(dimensions=2, length=3, scale=1.)
spinless = True
geometry = [('H', (0, 0)), ('H', (0.5, 0.8))]
fermion_hamiltonian = plane_wave_hamiltonian(grid,
geometry,
spinless,
False,
include_constant=True)
qubit_hamiltonian = jordan_wigner(fermion_hamiltonian)
test_hamiltonian = jordan_wigner_dual_basis_hamiltonian(
grid, geometry, spinless, include_constant=True)
self.assertTrue(test_hamiltonian.isclose(qubit_hamiltonian))
def test_qubit_jw_fermion_integration(self):
# Initialize a random fermionic operator.
fermion_operator = FermionOperator(((3, 1), (2, 1), (1, 0), (0, 0)),
-4.3)
fermion_operator += FermionOperator(((3, 1), (1, 0)), 8.17)
fermion_operator += 3.2 * FermionOperator()
# Map to qubits and compare matrix versions.
qubit_operator = jordan_wigner(fermion_operator)
qubit_sparse = get_sparse_operator(qubit_operator)
qubit_spectrum = sparse_eigenspectrum(qubit_sparse)
fermion_sparse = jordan_wigner_sparse(fermion_operator)
fermion_spectrum = sparse_eigenspectrum(fermion_sparse)
self.assertAlmostEqual(
0., numpy.amax(numpy.absolute(fermion_spectrum - qubit_spectrum)))
def test_bk_jw_integration(self):
# This is a legacy test, which was a minimal failing example when
# optimization for hermitian operators was used.
n_qubits = 4
# Minimal failing example:
fo = FermionOperator(((3, 1), ))
jw = jordan_wigner(fo)
bk = bravyi_kitaev(fo)
jw_spectrum = eigenspectrum(jw)
bk_spectrum = eigenspectrum(bk)
self.assertAlmostEqual(
0., numpy.amax(numpy.absolute(jw_spectrum - bk_spectrum)))
def test_bk_jw_number_operators(self):
# Check if a number operator has the same spectrum in both
# JW and BK representations
n_qubits = 2
n1 = number_operator(n_qubits, 0)
n2 = number_operator(n_qubits, 1)
n = n1 + n2
jw_n = jordan_wigner(n)
bk_n = bravyi_kitaev(n)
# Diagonalize and make sure the spectra are the same.
jw_spectrum = eigenspectrum(jw_n)
bk_spectrum = eigenspectrum(bk_n)
self.assertAlmostEqual(
0., numpy.amax(numpy.absolute(jw_spectrum - bk_spectrum)))
def test_bk_jw_integration_original(self):
# This is a legacy test, which was an example proposed by Ryan,
# failing when optimization for hermitian operators was used.
n_qubits = 5
fermion_operator = FermionOperator(((3, 1), (2, 1), (1, 0), (0, 0)),
-4.3)
fermion_operator += FermionOperator(((3, 1), (1, 0)), 8.17)
fermion_operator += 3.2 * FermionOperator()
# Map to qubits and compare matrix versions.
jw_qubit_operator = jordan_wigner(fermion_operator)
bk_qubit_operator = bravyi_kitaev(fermion_operator)
# Diagonalize and make sure the spectra are the same.
jw_spectrum = eigenspectrum(jw_qubit_operator)
bk_spectrum = eigenspectrum(bk_qubit_operator)
self.assertAlmostEqual(0., numpy.amax(numpy.absolute(jw_spectrum -
bk_spectrum)))
def benchmark_molecular_operator_jordan_wigner(n_qubits):
"""Test speed with which molecular operators transform to qubit operators.
Args:
n_qubits: The size of the molecular operator instance. Ideally, we
would be able to transform to a qubit operator for 50 qubit
instances in less than a minute. We are way too slow right now.
Returns:
runtime: The number of seconds required to make the conversion.
"""
# Get an instance of InteractionOperator.
molecular_operator = artificial_molecular_operator(n_qubits)
# Convert to a qubit operator.
start = time.time()
qubit_operator = jordan_wigner(molecular_operator)
end = time.time()
# Return runtime.
runtime = end - start
return runtime
