def test_collapse_gate(backend, nqubits, targets, results, oncircuit):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_state = utils.random_numpy_state(nqubits)
if oncircuit:
c = Circuit(nqubits)
c.add(gates.Collapse(*targets, result=results))
final_state = c(np.copy(initial_state)).numpy()
else:
collapse = gates.Collapse(*targets, result=results)
if backend == "custom":
final_state = collapse(np.copy(initial_state)).numpy()
else:
original_shape = initial_state.shape
new_shape = nqubits * (2, )
final_state = collapse(np.copy(initial_state).reshape(new_shape))
final_state = final_state.numpy().reshape(original_shape)
if isinstance(results, int):
results = nqubits * [results]
slicer = nqubits * [slice(None)]
for t, r in zip(targets, results):
slicer[t] = r
slicer = tuple(slicer)
initial_state = initial_state.reshape(nqubits * (2, ))
target_state = np.zeros_like(initial_state)
target_state[slicer] = initial_state[slicer]
norm = (np.abs(target_state)**2).sum()
target_state = target_state.ravel() / np.sqrt(norm)
np.testing.assert_allclose(final_state, target_state)
qibo.set_backend(original_backend)
def test_qaoa_execution(solver, trotter, accelerators):
h = hamiltonians.TFIM(4, h=1.0, trotter=trotter)
m = hamiltonians.X(4, trotter=trotter)
# Trotter and RK require small p's!
params = 0.01 * (1 - 2 * np.random.random(4))
state = utils.random_numpy_state(4)
# set absolute test tolerance according to solver
if "rk" in solver:
atol = 1e-2
elif trotter:
atol = 1e-5
else:
atol = 0
target_state = np.copy(state)
h_matrix = h.matrix.numpy()
m_matrix = m.matrix.numpy()
for i, p in enumerate(params):
if i % 2:
u = expm(-1j * p * m_matrix)
else:
u = expm(-1j * p * h_matrix)
target_state = u @ target_state
qaoa = models.QAOA(h, mixer=m, solver=solver, accelerators=accelerators)
qaoa.set_parameters(params)
final_state = qaoa(np.copy(state))
np.testing.assert_allclose(final_state, target_state, atol=atol)
def assert_gates_equivalent(qibo_gate,
cirq_gates,
nqubits,
ndevices=None,
atol=1e-7):
"""Asserts that QIBO and Cirq gates have equivalent action on a random state.
Args:
qibo_gate: QIBO gate.
cirq_gates: List of tuples (cirq gate, target qubit IDs).
nqubits: Total number of qubits in the circuit.
atol: Absolute tolerance in state vector comparsion.
"""
initial_state = utils.random_numpy_state(nqubits)
target_state = execute_cirq(cirq_gates, nqubits, np.copy(initial_state))
accelerators = None if ndevices is None else {"/GPU:0": ndevices}
if isinstance(qibo_gate, native_gates.TensorflowGate) and accelerators:
with pytest.raises(NotImplementedError):
c = models.Circuit(nqubits, accelerators)
c.add(qibo_gate)
else:
c = models.Circuit(nqubits, accelerators)
c.add(qibo_gate)
final_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(target_state, final_state, atol=atol)
def test_qaoa_callbacks(accelerators):
from qibo import callbacks
# use ``Y`` Hamiltonian so that there are no errors
# in the Trotter decomposition
h = hamiltonians.Y(3)
energy = callbacks.Energy(h)
params = 0.1 * np.random.random(4)
state = utils.random_numpy_state(3)
ham = hamiltonians.Y(3, trotter=True)
qaoa = models.QAOA(ham, callbacks=[energy], accelerators=accelerators)
qaoa.set_parameters(params)
final_state = qaoa(np.copy(state))
h_matrix = h.matrix.numpy()
m_matrix = qaoa.mixer.matrix.numpy()
calc_energy = lambda s: (s.conj() * h_matrix.dot(s)).sum()
target_state = np.copy(state)
target_energy = [calc_energy(target_state)]
for i, p in enumerate(params):
if i % 2:
u = expm(-1j * p * m_matrix)
else:
u = expm(-1j * p * h_matrix)
target_state = u @ target_state
target_energy.append(calc_energy(target_state))
np.testing.assert_allclose(energy[:], target_energy)
def test_controlled_by_unitary_action(backend):
qibo.set_backend(backend)
init_state = utils.random_numpy_state(2)
gate = gates.RX(1, theta=0.1234).controlled_by(0)
c = Circuit(2)
c.add(gate)
target_state = c(np.copy(init_state)).numpy()
final_state = gate.unitary.numpy().dot(init_state)
np.testing.assert_allclose(final_state, target_state)
def test_distributed_qft_agreement(nqubits):
"""Check ``_DistributedQFT`` agrees with normal ``QFT``."""
initial_state = utils.random_numpy_state(nqubits)
exact_state = exact_qft(initial_state)
c = models._DistributedQFT(nqubits)
final_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(final_state, exact_state, atol=_atol)
def test_qft(backend, nqubits, accelerators):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_state = utils.random_numpy_state(nqubits)
c = models.QFT(nqubits, accelerators=accelerators)
final_state = c(np.copy(initial_state)).numpy()
cirq_gates = [(cirq.QFT, list(range(nqubits)))]
target_state = execute_cirq(cirq_gates, nqubits, np.copy(initial_state))
np.testing.assert_allclose(target_state, final_state, atol=1e-6)
qibo.set_backend(original_backend)
def test_distributed_qft_execution(nqubits, accelerators):
original_backend = qibo.get_backend()
qibo.set_backend("custom")
dist_c = models.QFT(nqubits, accelerators=accelerators)
c = models.QFT(nqubits)
initial_state = utils.random_numpy_state(nqubits)
final_state = dist_c(initial_state).numpy()
target_state = c(initial_state).numpy()
np.testing.assert_allclose(target_state, final_state)
qibo.set_backend(original_backend)
def test_controlled_rotations_from_un(backend, name, params):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
init_state = utils.random_numpy_state(2)
gate = getattr(gates, name)(0, 1, **params)
c = Circuit(2)
c.add(gate)
target_state = c(np.copy(init_state)).numpy()
final_state = gate.unitary.numpy().dot(init_state)
np.testing.assert_allclose(final_state, target_state)
qibo.set_backend(original_backend)
def test_qft_transformation_random(nqubits):
"""Check QFT transformation for random initial state."""
initial_state = utils.random_numpy_state(nqubits)
exact_state = exact_qft(initial_state)
c_init = models.Circuit(nqubits)
c_init.add(gates.Flatten(initial_state))
c = c_init + models.QFT(nqubits)
final_state = c.execute().numpy()
np.testing.assert_allclose(final_state, exact_state, atol=_atol)
def test_controlled_by_unitary_action(backend):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
init_state = utils.random_numpy_state(2)
matrix = utils.random_numpy_complex((2, 2))
gate = gates.Unitary(matrix, 1).controlled_by(0)
c = Circuit(2)
c.add(gate)
target_state = c(np.copy(init_state)).numpy()
final_state = gate.unitary.numpy().dot(init_state)
np.testing.assert_allclose(final_state, target_state)
qibo.set_backend(original_backend)
def test_dagger_controlled_by(backend, gate, params):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
c = Circuit(4)
gate = getattr(gates, gate)(3, **params).controlled_by(0, 1, 2)
c.add((gate, gate.dagger()))
initial_state = utils.random_numpy_state(4)
final_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(final_state, initial_state)
qibo.set_backend(original_backend)
def test_dagger_one_qubit(backend, gate, params):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
c = Circuit(1)
gate = getattr(gates, gate)(0, **params)
c.add((gate, gate.dagger()))
initial_state = utils.random_numpy_state(1)
final_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(final_state, initial_state)
qibo.set_backend(original_backend)
def test_variational_layer_dagger(backend, nqubits):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
theta = 2 * np.pi * np.random.random((2, nqubits))
pairs = list((i, i + 1) for i in range(0, nqubits - 1, 2))
gate = gates.VariationalLayer(range(nqubits), pairs, gates.RY, gates.CZ,
theta[0], theta[1])
c = Circuit(nqubits)
c.add((gate, gate.dagger()))
initial_state = utils.random_numpy_state(nqubits)
final_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(final_state, initial_state)
qibo.set_backend(original_backend)
def test_unitary_controlled_by_dagger(backend):
from scipy.linalg import expm
original_backend = qibo.get_backend()
qibo.set_backend(backend)
matrix = np.random.random((2, 2))
matrix = expm(1j * (matrix + matrix.T))
gate = gates.Unitary(matrix, 0).controlled_by(1, 2, 3, 4)
c = Circuit(5)
c.add((gate, gate.dagger()))
initial_state = utils.random_numpy_state(5)
final_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(final_state, initial_state)
qibo.set_backend(original_backend)
def test_density_matrix_circuit_initial_state(backend):
"""Check that circuit transforms state vector initial state to density matrix."""
import tensorflow as tf
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_psi = utils.random_numpy_state(3)
c = models.Circuit(3, density_matrix=True)
final_rho = c(np.copy(initial_psi))
target_rho = np.outer(initial_psi, initial_psi.conj())
np.testing.assert_allclose(final_rho, target_rho)
initial_psi = tf.cast(initial_psi, dtype=final_rho.dtype)
final_rho = c(initial_psi)
np.testing.assert_allclose(final_rho, target_rho)
qibo.set_backend(original_backend)
def test_user_initialization(nqubits):
import itertools
target_state = utils.random_numpy_state(nqubits)
devices = {"/GPU:0": 2, "/GPU:1": 2}
c = models.DistributedCircuit(nqubits, devices)
c.queues.qubits = distutils.DistributedQubits(range(c.nglobal), c.nqubits)
state = c.get_initial_state(target_state)
np.testing.assert_allclose(state.numpy(), target_state)
target_state = target_state.reshape(nqubits * (2, ))
for i, s in enumerate(itertools.product([0, 1], repeat=c.nglobal)):
piece = state.pieces[i].numpy()
target_piece = target_state[s]
np.testing.assert_allclose(target_piece.ravel(), piece)
def test_collapse_gate(backend, nqubits, targets, results):
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_psi = utils.random_numpy_state(nqubits)
initial_rho = np.outer(initial_psi, initial_psi.conj())
c = models.Circuit(nqubits, density_matrix=True)
c.add(gates.Collapse(*targets, result=results))
final_rho = c(np.copy(initial_rho))
c = models.Circuit(nqubits)
c.add(gates.Collapse(*targets, result=results))
target_psi = c(np.copy(initial_psi)).numpy()
target_rho = np.outer(target_psi, target_psi.conj())
np.testing.assert_allclose(final_rho, target_rho)
qibo.set_backend(original_backend)
def test_x_decomposition_execution(target, controls, free, use_toffolis):
"""Check that applying the decomposition is equivalent to applying the multi-control gate."""
gate = gates.X(target).controlled_by(*controls)
nqubits = max((target, ) + controls + free) + 1
init_state = utils.random_numpy_state(nqubits)
targetc = Circuit(nqubits)
targetc.add(gate)
target_state = targetc(np.copy(init_state)).numpy()
c = Circuit(nqubits)
c.add(gate.decompose(*free, use_toffolis=use_toffolis))
final_state = c(np.copy(init_state)).numpy()
np.testing.assert_allclose(final_state, target_state, atol=_ATOL)
def test_collapse_gate_distributed(accelerators, nqubits, targets):
initial_state = utils.random_numpy_state(nqubits)
c = Circuit(nqubits, accelerators)
c.add(gates.Collapse(*targets))
final_state = c(np.copy(initial_state)).numpy()
slicer = nqubits * [slice(None)]
for t in targets:
slicer[t] = 0
slicer = tuple(slicer)
initial_state = initial_state.reshape(nqubits * (2, ))
target_state = np.zeros_like(initial_state)
target_state[slicer] = initial_state[slicer]
norm = (np.abs(target_state)**2).sum()
target_state = target_state.ravel() / np.sqrt(norm)
np.testing.assert_allclose(final_state, target_state)
def test_simple_execution_global(ndevices):
original_backend = qibo.get_backend()
qibo.set_backend("custom")
devices = {"/GPU:0": ndevices // 2, "/GPU:1": ndevices // 2}
dist_c = models.DistributedCircuit(6, devices)
dist_c.add((gates.H(i) for i in range(6)))
c = models.Circuit(6)
c.add((gates.H(i) for i in range(6)))
initial_state = utils.random_numpy_state(c.nqubits)
final_state = dist_c(np.copy(initial_state)).numpy()
target_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(target_state, final_state)
qibo.set_backend(original_backend)
def test_toffoli_gate(backend):
"""Check applying Toffoli to three qubit density matrix."""
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_psi = utils.random_numpy_state(3)
initial_rho = np.outer(initial_psi, initial_psi.conj())
circuit = models.Circuit(3, density_matrix=True)
circuit.add(gates.TOFFOLI(0, 2, 1))
final_rho = circuit(np.copy(initial_rho)).numpy()
circuit = models.Circuit(3)
circuit.add(gates.TOFFOLI(0, 2, 1))
target_psi = circuit(np.copy(initial_psi)).numpy()
target_rho = np.outer(target_psi, target_psi.conj())
np.testing.assert_allclose(final_rho, target_rho)
qibo.set_backend(original_backend)
def test_one_qubit_gates(backend, gatename, gatekwargs):
"""Check applying one qubit gates to one qubit density matrix."""
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_psi = utils.random_numpy_state(1)
initial_rho = np.outer(initial_psi, initial_psi.conj())
circuit = models.Circuit(1, density_matrix=True)
circuit.add(getattr(gates, gatename)(0, **gatekwargs))
final_rho = circuit(np.copy(initial_rho)).numpy()
circuit = models.Circuit(1)
circuit.add(getattr(gates, gatename)(0, **gatekwargs))
target_psi = circuit(np.copy(initial_psi)).numpy()
target_rho = np.outer(target_psi, target_psi.conj())
np.testing.assert_allclose(final_rho, target_rho)
qibo.set_backend(original_backend)
def test_u2(backend):
"""Check U2 gate on random state."""
original_backend = qibo.get_backend()
qibo.set_backend(backend)
phi = 0.1234
lam = 0.4321
initial_state = utils.random_numpy_state(1)
c = Circuit(1)
c.add(gates.U2(0, phi, lam))
final_state = c(np.copy(initial_state))
matrix = np.array([[np.exp(-1j * (phi + lam) / 2), -np.exp(-1j * (phi - lam) / 2)],
[np.exp(1j * (phi - lam) / 2), np.exp(1j * (phi + lam) / 2)]])
target_state = matrix.dot(initial_state) / np.sqrt(2)
np.testing.assert_allclose(final_state, target_state)
qibo.set_backend(original_backend)
def test_controlled_execution(ndevices):
original_backend = qibo.get_backend()
qibo.set_backend("custom")
devices = {"/GPU:0": ndevices}
dist_c = models.DistributedCircuit(4, devices)
dist_c.add((gates.H(i) for i in range(dist_c.nglobal, 4)))
dist_c.add(gates.CNOT(0, 2))
c = models.Circuit(4)
c.add((gates.H(i) for i in range(dist_c.nglobal, 4)))
c.add(gates.CNOT(0, 2))
initial_state = utils.random_numpy_state(c.nqubits)
final_state = dist_c(np.copy(initial_state)).numpy()
target_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(target_state, final_state)
qibo.set_backend(original_backend)
def test_controlled_by_random(backend, nqubits):
"""Check controlled_by method on gate."""
original_backend = qibo.get_backend()
qibo.set_backend(backend)
initial_psi = utils.random_numpy_state(nqubits)
initial_rho = np.outer(initial_psi, initial_psi.conj())
c = models.Circuit(nqubits, density_matrix=True)
c.add(gates.RX(1, theta=0.789).controlled_by(2))
c.add(gates.fSim(0, 2, theta=0.123, phi=0.321).controlled_by(1, 3))
final_rho = c(np.copy(initial_rho)).numpy()
c = models.Circuit(nqubits)
c.add(gates.RX(1, theta=0.789).controlled_by(2))
c.add(gates.fSim(0, 2, theta=0.123, phi=0.321).controlled_by(1, 3))
target_psi = c(np.copy(initial_psi)).numpy()
target_rho = np.outer(target_psi, target_psi.conj())
np.testing.assert_allclose(final_rho, target_rho)
qibo.set_backend(original_backend)
def test_cz(backend):
"""Check CZ gate is working properly on random state."""
original_backend = qibo.get_backend()
qibo.set_backend(backend)
init_state = utils.random_numpy_state(2)
matrix = np.eye(4)
matrix[3, 3] = -1
target_state = matrix.dot(init_state)
c = Circuit(2)
c.add(gates.CZ(0, 1))
final_state = c.execute(np.copy(init_state)).numpy()
np.testing.assert_allclose(final_state, target_state)
c = Circuit(2)
c.add(gates.Z(1).controlled_by(0))
final_state = c.execute(np.copy(init_state)).numpy()
assert c.queue[0].name == "cz"
np.testing.assert_allclose(final_state, target_state)
qibo.set_backend(original_backend)
def test_execution_with_global_swap():
original_backend = qibo.get_backend()
qibo.set_backend("custom")
devices = {"/GPU:0": 2, "/GPU:1": 1, "/GPU:2": 1}
dist_c = models.DistributedCircuit(6, devices)
dist_c.add((gates.H(i) for i in range(6)))
dist_c.add((gates.SWAP(i, i + 1) for i in range(5)))
dist_c.global_qubits = [0, 1]
c = models.Circuit(6)
c.add((gates.H(i) for i in range(6)))
c.add((gates.SWAP(i, i + 1) for i in range(5)))
initial_state = utils.random_numpy_state(c.nqubits)
final_state = dist_c(np.copy(initial_state)).numpy()
target_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(target_state, final_state)
qibo.set_backend(original_backend)
def test_generalizedfsim_dagger(backend, tfmatrix):
from scipy.linalg import expm
original_backend = qibo.get_backend()
qibo.set_backend(backend)
phi = 0.2
matrix = np.random.random((2, 2))
matrix = expm(1j * (matrix + matrix.T))
if tfmatrix:
import tensorflow as tf
from qibo.config import DTYPES
matrix = tf.cast(matrix, dtype=DTYPES.get('DTYPECPX'))
gate = gates.GeneralizedfSim(0, 1, matrix, phi)
c = Circuit(2)
c.add((gate, gate.dagger()))
initial_state = utils.random_numpy_state(2)
final_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(final_state, initial_state)
qibo.set_backend(original_backend)
def test_controlled_execution_large(ndevices):
devices = {"/GPU:0": ndevices // 2, "/GPU:1": ndevices // 2}
dist_c = models.DistributedCircuit(6, devices)
dist_c.add([gates.H(0), gates.H(2), gates.H(3)])
dist_c.add(gates.CNOT(4, 5))
dist_c.add(gates.Z(1).controlled_by(0))
dist_c.add(gates.SWAP(2, 3))
dist_c.add([gates.X(2), gates.X(3), gates.X(4)])
c = models.Circuit(6)
c.add([gates.H(0), gates.H(2), gates.H(3)])
c.add(gates.CNOT(4, 5))
c.add(gates.Z(1).controlled_by(0))
c.add(gates.SWAP(2, 3))
c.add([gates.X(2), gates.X(3), gates.X(4)])
initial_state = utils.random_numpy_state(c.nqubits)
final_state = dist_c(np.copy(initial_state)).numpy()
target_state = c(np.copy(initial_state)).numpy()
np.testing.assert_allclose(target_state, final_state)
