def test_hessian_based_methods(simulator, method, use_hessian):
wfn = tq.QubitWaveFunction.from_string(string="1.0*|00> + 1.0*|11>")
H = tq.paulis.Projector(wfn=wfn.normalize())
U = tq.gates.Ry(angle=tq.assign_variable("a") * numpy.pi, target=0)
U += tq.gates.Ry(angle=tq.assign_variable("b") * numpy.pi,
target=1,
control=0)
E = tq.ExpectationValue(H=H, U=U)
method_options = {"gtol": 1.e-4}
# need to improve starting points for some of the optimizations
initial_values = {"a": 0.002, "b": 0.01}
if method not in ["TRUST-CONSTR", "TRUST_KRYLOV]"]:
method_options['eta'] = 0.1
method_options['initial_trust_radius'] = 0.1
method_options['max_trust_radius'] = 0.25
initial_values = {"a": 0.3, "b": 0.8}
# numerical hessian only works for this method
if use_hessian in ['2-point', '3-point']:
if method != "TRUST-CONSTR":
return
initial_values = {"a": 0.3, "b": 0.8}
result = tq.optimizer_scipy.minimize(objective=-E,
backend=simulator,
hessian=use_hessian,
method=method,
tol=1.e-4,
method_options=method_options,
initial_values=initial_values,
silent=True)
assert (numpy.isclose(result.energy, -1.0, atol=1.e-1))
def test_gradient_based_methods(simulator, method, use_gradient):
wfn = tq.QubitWaveFunction.from_string(string="1.0*|00> + 1.0*|11>")
H = tq.paulis.Projector(wfn=wfn.normalize())
U = tq.gates.Ry(angle=tq.assign_variable("a") * numpy.pi, target=0)
U += tq.gates.Ry(angle=tq.assign_variable("b") * numpy.pi,
target=1,
control=0)
E = tq.ExpectationValue(H=H, U=U)
# need to improve starting points for some of the optimizations
initial_values = {"a": 0.002, "b": 0.01}
if method in ["L-BFGS-B", "TNC"]:
initial_values = {"a": 0.1, "b": 0.8}
if use_gradient is False:
initial_values = {"a": 0.3, "b": 0.8}
result = tq.optimizer_scipy.minimize(objective=-E,
backend=simulator,
gradient=use_gradient,
method=method,
tol=1.e-4,
method_options={
"gtol": 1.e-4,
"eps": 1.e-4
},
initial_values=initial_values,
silent=True)
assert (numpy.isclose(result.energy, -1.0, atol=1.e-1))
def test_gradient_based_methods(simulator, method, use_gradient):
wfn = tq.QubitWaveFunction.from_string(string="1.0*|00> + 1.0*|11>")
H = tq.paulis.Projector(wfn=wfn.normalize())
U = tq.gates.Ry(angle=tq.assign_variable("a") * numpy.pi, target=0)
U += tq.gates.Ry(angle=tq.assign_variable("b") * numpy.pi,
target=1,
control=0)
E = tq.ExpectationValue(H=H, U=U)
initial_values = {"a": 3.45, "b": 2.85}
# eps is absolute finite difference step of scipy (used only for gradient = False or scipy < 1.5)
# finite_diff_rel_step is relative step
result = tq.optimizer_scipy.minimize(objective=-E,
backend=simulator,
gradient=use_gradient,
method=method,
tol=1.e-3,
method_options={
"gtol": 1.e-4,
"eps": 1.e-4,
"finite_diff_rel_step": 1.e-4
},
initial_values=initial_values,
silent=True)
assert (numpy.isclose(result.energy, -1.0, atol=1.e-1))
def test_moments():
c = QCircuit()
c += CNOT(target=0, control=(1, 2, 3))
c += H(target=[0, 1])
c += Rx(angle=numpy.pi, target=[0, 3])
c += Z(target=1)
c += Phase(phi=numpy.pi, target=4)
moms = c.moments
assert len(moms) == 3
assert (moms[0].gates[1].parameter == assign_variable(numpy.pi))
assert (moms[0].gates[1].target == (4, ))
def test_canonical_moments():
c = QCircuit()
c += CNOT(target=0, control=(1, 2, 3))
c += Rx(angle=Variable('a'), target=[0, 3])
c += H(target=[0, 1])
c += Rx(angle=Variable('a'), target=[2, 3])
c += Rx(angle=Variable('a'), target=[0, 3])
c += Z(target=1)
c += Phase(phi=numpy.pi, target=4)
moms = c.canonical_moments
assert len(moms) == 6
assert (moms[0].gates[1].parameter == assign_variable(numpy.pi))
assert (moms[0].gates[1].target == (4, ))
assert hasattr(moms[3].gates[0], 'axis')
assert len(moms[0].qubits) == 5
def manual_ansatz(n_qubits, n_layers=1, connectivity=None, static=False):
# no pbc
U = tq.QCircuit()
for l in range(n_layers):
for q in range(n_qubits):
angle = (l,q,0) if not static else (l,0)
angle = tq.assign_variable(angle)
U += tq.gates.Ry(angle=angle*numpy.pi, target=q)
for q in range(n_qubits//2):
angle = (l, 2*q,2*q+1, 1) if not static else 1.0
angle = tq.assign_variable(angle)
U += tq.gates.ExpPauli(paulistring="X({})Y({})".format(2*q,2*q+1), angle=angle*numpy.pi)
#U += tq.gates.ExpPauli(paulistring="Y({})X({})".format(2*q,2*q+1), angle=angle*numpy.pi)
# for q in range(n_qubits):
# angle = (l, q,1) if not static else (l,1)
# U += tq.gates.Ry(angle=angle, target=q)
for q in range(n_qubits//2-1):
angle = (l, 2*q+1, 2*q+2, 1) if not static else 1.0
angle = tq.assign_variable(angle)
U += tq.gates.ExpPauli(paulistring="X({})Y({})".format(2*q+1,(2*q+2)%n_qubits), angle=angle*numpy.pi)
#U += tq.gates.ExpPauli(paulistring="Y({})X({})".format(2*q+1,(2*q+2)%n_qubits), angle=angle*numpy.pi)
return U