def test_paulistring_sampling(backend, case):
print(case)
H = QubitHamiltonian.from_paulistrings(PauliString.from_string(case[0]))
U = gates.X(target=1) + gates.X(target=3) + gates.X(target=5)
E = ExpectationValue(H=H, U=U)
result = simulate(E,backend=backend, samples=1)
assert isclose(result, case[1], 1.e-4)
def test_mixed_power(
simulator,
value1=(numpy.random.randint(0, 1000) / 1000.0 * (numpy.pi / 2.0)),
value2=(numpy.random.randint(0, 1000) / 1000.0 * (numpy.pi / 2.0))):
angle1 = Variable(name="angle1")
angle2 = Variable(name="angle2")
variables = {angle1: value1, angle2: value2}
qubit = 0
control = 1
H1 = paulis.X(qubit=qubit)
U1 = gates.X(target=control) + gates.Ry(
target=qubit, control=control, angle=angle1)
e1 = ExpectationValue(U=U1, H=H1)
H2 = paulis.Y(qubit=qubit)
U2 = gates.X(target=control) + gates.Rx(
target=qubit, control=control, angle=angle2)
e2 = ExpectationValue(U=U2, H=H2)
added = e1**e2
val = simulate(added, variables=variables, backend=simulator)
en1 = simulate(e1, variables=variables, backend=simulator)
en2 = simulate(e2, variables=variables, backend=simulator)
an1 = np.sin(angle1(variables=variables))
an2 = -np.sin(angle2(variables=variables))
assert np.isclose(val, en1**en2, atol=1.e-4)
assert np.isclose(val, an1**an2, atol=1.e-4)
def test_gradient_UY_HX(simulator, angle_value, controlled, silent=True):
# case X Y
# U = cos(angle/2) + sin(-angle/2)*i*Y
# <0|Ud H U |0> = cos^2(angle/2)*<0|X|0>
# + sin^2(-angle/2) <0|YXY|0>
# + cos(angle/2)*sin(angle/2)*i<0|XY|0>
# + sin(-angle/2)*cos(angle/2)*(-i) <0|YX|0>
# = cos^2*0 + sin^2*0 + cos*sin*i(<0|[XY,YX]|0>)
# = 0.5*sin(-angle)*i <0|[XY,YX]|0> = -0.5*sin(angle)*i * 2 i <0|Z|0>
# = sin(angle)
angle = Variable(name="angle")
variables = {angle: angle_value}
qubit = 0
H = paulis.X(qubit=qubit)
if controlled:
control = 1
U = gates.X(target=control) + gates.Ry(
target=qubit, control=control, angle=angle)
else:
U = gates.X(target=qubit) + gates.X(target=qubit) + gates.Ry(
target=qubit, angle=angle)
O = ExpectationValue(U=U, H=H)
E = simulate(O, variables=variables, backend=simulator)
print("O={type}".format(type=type(O)))
dO = grad(objective=O, variable=angle)
dE = simulate(dO, variables=variables, backend=simulator)
assert (numpy.isclose(E, numpy.sin(angle(variables)), atol=1.e-4))
assert (numpy.isclose(dE, numpy.cos(angle(variables)), atol=1.e-4))
if not silent:
print("E =", E)
print("sin(angle)=", numpy.sin(angle()))
print("dE =", dE)
print("cos(angle)=", numpy.cos(angle()))
def test_repetition_works(simulator, p):
qubit = 0
H = paulis.Qm(qubit)
U = gates.X(target=qubit) + gates.X(target=qubit)
O = ExpectationValue(U=U, H=H)
NM = BitFlip(p, 1)
E = simulate(O, backend=simulator, samples=1, noise=NM)
def test_compile_swap():
circuit = gates.SWAP(first=0, second=3)
equivalent_circuit = compile_swap(circuit)
equivalent_swap = gates.X(target=0, control=3) + gates.X(
target=3, control=0) + gates.X(target=0, control=3)
assert (equivalent_circuit == equivalent_swap)
def test_double_cnot_bit_flip(simulator, p):
qubit = 1
U = gates.X(0) + gates.X(2) + gates.CX(0, 1) + gates.CX(2, 1)
H = paulis.Qm(qubit)
O = ExpectationValue(U=U, H=H)
NM = BitFlip(p, 2)
E = simulate(O, backend=simulator, samples=1000, noise=NM)
assert (numpy.isclose(E, 2 * (p - p * p), atol=1.e-1))
def test_double_cnot_bit_flip(simulator, p):
qubit = 1
U = gates.X(0) + gates.X(2) + gates.CX(0, 1) + gates.CX(2, 1)
H = paulis.Qm(qubit)
O = ExpectationValue(U=U, H=H)
NM = BitFlip(p, 2)
E = simulate(O, backend=simulator, samples=1, noise=NM)
def test_controls(target, control, gate):
c0 = gates.X(target=control) + gate(target=target, control=None)
c1 = gates.X(target=control) + gate(target=target, control=control)
wfn0 = simulate(c0, initial_state=0, backend="symbolic")
wfn1 = simulate(c1, initial_state=0, backend="symbolic")
assert (wfn0.isclose(wfn1))
c0 = gates.QCircuit()
c1 = gate(target=target, control=control)
wfn0 = simulate(c0, initial_state=0)
wfn1 = simulate(c1, initial_state=0)
assert (wfn0.isclose(wfn1))
def test_depolarizing_error(simulator, p, controlled):
cq = 1
qubit = 0
H = paulis.Z(0)
if controlled:
U = gates.X(target=cq) + gates.X(target=qubit, control=cq)
NM = DepolarizingError(p, 2)
else:
U = gates.X(target=qubit)
NM = DepolarizingError(p, 1)
O = ExpectationValue(U=U, H=H)
E = simulate(O, backend=simulator, samples=1, noise=NM)
def test_bit_flip(simulator, p, controlled):
qubit = 0
if controlled:
U = gates.X(target=1) + gates.CX(1, 0)
H = paulis.Qm(0)
NM = BitFlip(p, 2)
else:
U = gates.X(target=0)
NM = BitFlip(p, 1)
H = paulis.Qm(qubit)
O = ExpectationValue(U=U, H=H)
E = simulate(O, backend=simulator, samples=1, noise=NM)
def test_bit_flip(simulator, p, controlled):
qubit = 0
if controlled:
U = gates.X(target=1) + gates.CX(1, 0)
H = paulis.Qm(0)
NM = BitFlip(p, 2)
else:
U = gates.X(target=0)
NM = BitFlip(p, 1)
H = paulis.Qm(qubit)
O = ExpectationValue(U=U, H=H)
E = simulate(O, backend=simulator, samples=1000, noise=NM)
assert (numpy.isclose(E, 1.0 - p, atol=1.e-1))
def test_gradient_H(simulator, power, controlled):
qubit = 0
control = 1
angle = Variable(name="angle")
variables = {angle: power}
H = paulis.X(qubit=qubit)
if not controlled:
U = gates.H(target=qubit, power=angle)
else:
U = gates.X(target=control) + gates.H(
target=qubit, control=control, power=angle)
O = ExpectationValue(U=U, H=H)
E = simulate(O, variables=variables, backend=simulator)
assert (numpy.isclose(E,
-numpy.cos(angle(variables) * (numpy.pi)) / 2 + 0.5,
atol=1.e-4))
dO = grad(objective=O, variable=angle)
dE = simulate(dO, variables=variables, backend=simulator)
assert (numpy.isclose(dE,
numpy.pi * numpy.sin(angle(variables) * (numpy.pi)) /
2,
atol=1.e-4))
def test_gradient_UX_HY_wfnsim(simulator, angle, controlled, silent=True):
# same as before just with wavefunction simulation
# case YX
# U = cos(angle/2) + sin(-angle/2)*i*X
# O = cos*sin*i*<0|YX|0> + sin*cos*(-i)<0|XY|0>
# = 0.5*sin(-angle)*i <0|[YX,XY]|0>
# = -sin(angle)
angle_value = angle
angle = Variable(name="angle")
variables = {angle: angle_value}
qubit = 0
H = paulis.Y(qubit=qubit)
if controlled:
control = 1
U = gates.X(target=control) + gates.Rx(
target=qubit, control=control, angle=angle)
else:
U = gates.Rx(target=qubit, angle=angle)
O = ExpectationValue(U=U, H=H)
E = simulate(O, variables=variables, backend=simulator)
dO = grad(objective=O, variable=angle)
dE = simulate(dO, variables=variables)
assert (numpy.isclose(E, -numpy.sin(angle(variables)), atol=0.0001))
assert (numpy.isclose(dE, -numpy.cos(angle(variables)), atol=0.0001))
if not silent:
print("E =", E)
print("-sin(angle)=", -numpy.sin(angle(variables)))
print("dE =", dE)
print("-cos(angle)=", -numpy.cos(angle(variables)))
def test_gradient_PHASE_HY(simulator, angle_value, controlled, silent=False):
angle = Variable(name="angle")
variables = {angle: angle_value}
qubit = 0
H = paulis.Y(qubit=qubit)
if controlled:
control = 1
U = gates.X(target=control) + gates.H(target=qubit) + gates.Phase(
target=qubit, control=control, phi=angle) + gates.H(target=qubit)
else:
U = gates.H(target=qubit) + gates.Phase(
target=qubit, phi=angle) + gates.H(target=qubit)
O = ExpectationValue(U=U, H=H)
E = simulate(O, variables=variables, backend=simulator)
dO = grad(objective=O, variable='angle')
dE = simulate(dO, variables=variables)
assert (numpy.isclose(E, -numpy.sin(angle(variables)), atol=1.e-4))
assert (numpy.isclose(dE, -numpy.cos(angle(variables)), atol=1.e-4))
if not silent:
print("E =", E)
print("-sin(angle)=", -numpy.sin(angle(variables)))
print("dE =", dE)
print("-cos(angle)=", -numpy.cos(angle(variables)))
def test_phase_amp_damp(simulator, p):
qubit = 0
H = paulis.Z(0)
U = gates.X(target=qubit)
O = ExpectationValue(U=U, H=H)
NM = PhaseAmplitudeDamp(p, 1 - p, 1)
E = simulate(O, backend=simulator, samples=1, noise=NM)
def test_amp_damp(simulator, p):
qubit = 0
H = (0.5) * (paulis.I(0) - paulis.Z(0))
U = gates.X(target=qubit)
O = ExpectationValue(U=U, H=H)
NM = AmplitudeDamp(p, 1)
E = simulate(O, backend=simulator, samples=1, noise=NM)
def test_compilation(backend):
U = gates.X(target=[0, 1, 2, 3, 4, 5])
for i in range(10):
U += gates.Ry(angle=(i, ), target=numpy.random.randint(0, 5, 1)[0])
U += gates.CZ(0, 1) + gates.CNOT(1, 2) + gates.CZ(2, 3) + gates.CNOT(
3, 4) + gates.CZ(5, 6)
H = paulis.X(0) + paulis.X(1) + paulis.X(2) + paulis.X(3) + paulis.X(
4) + paulis.X(5)
H += paulis.Z(0) + paulis.Z(1) + paulis.Z(2) + paulis.Z(3) + paulis.Z(
4) + paulis.Z(5)
E = ExpectationValue(H=H, U=U)
randvals = numpy.random.uniform(0.0, 2.0, 10)
variables = {(i, ): randvals[i] for i in range(10)}
e0 = simulate(E, variables=variables, backend=backend)
E2 = E * E
for i in range(99):
E2 += E * E
compiled = tq.compile(E2, variables=variables, backend=backend)
e2 = compiled(variables=variables)
assert (E2.count_expectationvalues(unique=True) == 1)
assert (compiled.count_expectationvalues(unique=True) == 1)
assert numpy.isclose(100 * e0**2, e2)
def test_endianness_simulators():
tests = ["000111",
"111000",
"101010",
"010101",
"10010010001",
"111100101000010"]
for string in tests:
binary = BitString.from_binary(binary=string)
c = QCircuit()
for i, v in enumerate(binary):
if v == 1:
c += gates.X(target=i)
if v == 0:
c += gates.Z(target=i)
wfn_cirq = simulate(c, initial_state=0, backend="cirq")
counts_cirq = simulate(c, samples=1, backend="cirq")
counts_qiskit = simulate(c, samples=1, backend="qiskit")
print("counts_cirq =", type(counts_cirq))
print("counts_qiskit=", type(counts_qiskit))
print("counts_cirq =", counts_cirq)
print("counts_qiskit=", counts_qiskit)
assert (counts_cirq.isclose(counts_qiskit))
assert (wfn_cirq.state == counts_cirq.state)
def test_gradient_deep_H(simulator, power, controls):
if controls > 2 and simulator == "qiskit":
# does not work yet
return
qubit = 0
angle = Variable(name="angle")
variables = {angle: power}
control = [i for i in range(1, controls + 1)]
H = paulis.X(qubit=qubit)
U = gates.X(target=control) + gates.H(
target=qubit, control=control, power=angle)
O = ExpectationValue(U=U, H=H)
E = simulate(O, variables=variables, backend=simulator)
assert (numpy.isclose(E,
-numpy.cos(angle(variables) * (numpy.pi)) / 2 + 0.5,
atol=1.e-4))
dO = grad(objective=O, variable=angle)
dE = simulate(dO, variables=variables, backend=simulator)
assert (numpy.isclose(dE,
numpy.pi * numpy.sin(angle(variables) * (numpy.pi)) /
2,
atol=1.e-4))
def test_endianness_simulators():
tests = [
"000111", "111000", "101010", "010101", "10010010001",
"111100101000010"
]
for string in tests:
number = int(string, 2)
binary = BitString.from_binary(binary=string)
c = QCircuit()
for i, v in enumerate(binary):
if v == 1:
c += gates.X(target=i)
c += gates.Measurement(target=[x for x in range(len(string))])
wfn_cirq = simulate(c, initial_state=0, backend="cirq")
counts_cirq = simulate(c, samples=1, backend="cirq")
counts_qiskit = simulate(c, samples=1, backend="qiskit")
print("counts_cirq =", type(counts_cirq))
print("counts_qiskit=", type(counts_qiskit))
print("counts_cirq =", counts_cirq)
print("counts_qiskit=", counts_qiskit)
assert (counts_cirq == counts_qiskit)
assert (wfn_cirq.state == counts_cirq.state)
def test_rz_phase_flip_1(simulator, p, angle):
U = gates.X(target=0) + gates.H(1) + gates.CRz(control=0, target=1, angle=Variable('a')) + gates.H(1)
H = paulis.Z(1) * paulis.I(0)
O = ExpectationValue(U, H)
NM = PhaseFlip(p, 2)
E = simulate(O, backend=simulator, variables={'a': angle}, samples=1000, noise=NM)
print(E)
assert (numpy.isclose(E, ((1.0 - 2 * p) ** 2) * numpy.cos(angle), atol=1.e-1))
def test_qubit_excitations():
H = paulis.Projector("1.0*|100>")
U1 = gates.X(0) + gates.QubitExcitation(
target=[0, 1], angle="a", assume_real=True)
U2 = gates.X(0) + gates.Trotterized(
generators=[U1.gates[1].make_generator()], angles=["a"], steps=1)
E1 = ExpectationValue(H=H, U=U1)
E2 = ExpectationValue(H=H, U=U2)
dE1 = grad(E1, "a")
dE2 = grad(E2, "a")
for a in numpy.random.uniform(-numpy.pi, numpy.pi, 5):
a = float(a)
variables = {"a": a}
wfn1 = simulate(U1, variables=variables)
wfn2 = simulate(U2, variables=variables)
F = numpy.abs(wfn1.inner(wfn2))**2
assert numpy.isclose(F, 1.0, 1.e-4)
eval1 = simulate(dE1, variables=variables)
eval2 = simulate(dE2, variables=variables)
assert numpy.isclose(eval1, eval2, 1.e-4)
H = paulis.Projector("1.0*|0110>")
U1 = gates.X([1, 2]) + gates.QubitExcitation(
target=[0, 1, 3, 2], angle="a", assume_real=True)
U2 = gates.X([1, 2]) + gates.Trotterized(
generators=[U1.gates[2].make_generator()], angles=["a"], steps=1)
E1 = ExpectationValue(H=H, U=U1)
E2 = ExpectationValue(H=H, U=U2)
dE1 = grad(E1, "a")
dE2 = grad(E2, "a")
for a in numpy.random.uniform(-numpy.pi, numpy.pi, 5):
a = float(a)
variables = {"a": a}
wfn1 = simulate(U1, variables=variables)
wfn2 = simulate(U2, variables=variables)
F = numpy.abs(wfn1.inner(wfn2))**2
assert numpy.isclose(F, 1.0, 1.e-4)
eval1 = simulate(dE1, variables=variables)
eval2 = simulate(dE2, variables=variables)
assert numpy.isclose(eval1, eval2, 1.e-4)
def test_rx_bit_flip_1(simulator, p, angle):
U = gates.X(target=0) + gates.CRx(control=0, target=1, angle="a")
H = paulis.Z(1) * paulis.I(0)
NM = BitFlip(p, 2)
O = ExpectationValue(U=U, H=H)
E = simulate(O, backend=simulator, samples=1000, variables={'a': angle}, noise=NM)
print(E)
print(p + numpy.cos(angle) - p * numpy.cos(angle))
assert (numpy.isclose(E, p + numpy.cos(angle) - p * numpy.cos(angle), atol=1.e-1))
def test_phase_amp_damp_is_both(simulator, p):
qubit = 0
H = paulis.Z(0)
U = gates.X(target=qubit)
O = ExpectationValue(U=U, H=H)
NM1 = PhaseDamp(1 - p, 1) + AmplitudeDamp(p, 1)
E1 = simulate(O, backend=simulator, samples=1, noise_model=NM1)
NM2 = PhaseAmplitudeDamp(p, 1 - p, 1)
E2 = simulate(O, backend=simulator, samples=1, noise_model=NM2)
def test_compile_y(target, control, power):
circuit = gates.Y(target=target, control=control, power=power)
equivalent_circuit_y = compile_y(circuit)
equivalent_y = gates.Rz(target=target, control=None, angle=-numpy.pi / 2) + \
gates.X(target=target, control=control, power=power) + \
gates.Rz(target=target, control=None, angle=numpy.pi / 2)
assert (equivalent_circuit_y == equivalent_y)
def test_controlled_rotations(simulator):
angles = uniform(0, 2 * pi, 5)
gs = [gates.Rx, gates.Ry, gates.Rz]
for angle in angles:
for gate in gs:
qubit = randint(0, 1)
control = randint(2, 3)
U = gates.X(target=control) + gate(target=qubit, control=control, angle=angle)
RCU = compile_controlled_rotation(gate=U)
wfn1 = simulate(U, initial_state=0, backend=simulator)
wfn2 = simulate(RCU, initial_state=0, backend=simulator)
assert (isclose(numpy.abs(wfn1.inner(wfn2)) ** 2, 1.0, atol=1.e-4))
def test_rz_phase_flip_1(simulator, p, angle):
U = gates.X(target=0) + gates.H(1) + gates.CRz(
control=0, target=1, angle=Variable('a')) + gates.H(1)
H = paulis.Z(1) * paulis.I(0)
O = ExpectationValue(U, H)
NM = PhaseFlip(p, 2)
E = simulate(O,
backend=simulator,
variables={'a': angle},
samples=1,
noise=NM)
print(E)
def test_l_division(simulator, value=numpy.random.uniform(0.0, 2.0*numpy.pi, 1)[0]):
angle1 = Variable(name="angle1")
variables = {angle1: value}
qubit = 0
control = 1
H1 = paulis.X(qubit=qubit)
U1 = gates.X(target=control) + gates.Ry(target=qubit, control=control, angle=angle1)
e1 = ExpectationValue(U=U1, H=H1)
added = e1 / 2
val = simulate(added, variables=variables, backend=simulator)
en1 = simulate(e1, variables=variables, backend=simulator) / 2
an1 = np.sin(value) / 2.
assert np.isclose(val, en1, atol=1.e-4)
assert np.isclose(val, an1, atol=1.e-4)
def test_l_addition(simulator, value=(numpy.random.randint(0, 1000) / 1000.0 * (numpy.pi / 2.0))):
angle1 = Variable(name="angle1")
variables = {angle1: value}
qubit = 0
control = 1
H1 = paulis.X(qubit=qubit)
U1 = gates.X(target=control) + gates.Ry(target=qubit, control=control, angle=angle1)
e1 = ExpectationValue(U=U1, H=H1)
added = e1 + 1
val = simulate(added, variables=variables, backend=simulator)
en1 = simulate(e1, variables=variables, backend=simulator) + 1.
an1 = np.sin(angle1(variables=variables)) + 1.
assert np.isclose(val, en1, atol=1.e-4)
assert np.isclose(val, an1, atol=1.e-4)
def test_r_power(simulator, value=numpy.random.uniform(0.1, 1.9*numpy.pi, 1)[0]):
angle1 = Variable(name="angle1")
variables = {angle1: value}
qubit = 0
control = 1
H1 = paulis.X(qubit=qubit)
U1 = gates.X(target=control) + gates.Ry(target=qubit, control=control, angle=angle1)
e1 = ExpectationValue(U=U1, H=H1)
added = 2 ** e1
val = simulate(added, variables=variables, backend=simulator)
en1 = 2 ** simulate(e1, variables=variables, backend=simulator)
an1 = 2. ** np.sin(angle1(variables=variables))
assert np.isclose(val, en1, atol=1.e-4)
assert np.isclose(val, an1, atol=1.e-4)
