def test_non_differentiable(self):
"""Test that a non-differentiable parameter is
correctly marked"""
with qml.tape.JacobianTape() as tape:
qml.FockState(1, wires=0)
qml.Displacement(0.543, 0, wires=[1])
qml.Beamsplitter(0, 0, wires=[0, 1])
qml.expval(qml.X(wires=[0]))
assert _grad_method(tape, 0) is None
assert _grad_method(tape, 1) == "A"
assert _grad_method(tape, 2) == "A"
assert _grad_method(tape, 3) == "A"
assert _grad_method(tape, 4) == "A"
_gradient_analysis(tape)
assert tape._par_info[0]["grad_method"] is None
assert tape._par_info[1]["grad_method"] == "A"
assert tape._par_info[2]["grad_method"] == "A"
assert tape._par_info[3]["grad_method"] == "A"
assert tape._par_info[4]["grad_method"] == "A"
_gradient_analysis(tape)
def test_unknown_op_grad_method(self, monkeypatch):
"""Test that an exception is raised if an operator has a
grad method defined that the CV parameter-shift tape
doesn't recognize"""
monkeypatch.setattr(qml.Rotation, "grad_method", "B")
with qml.tape.JacobianTape() as tape:
qml.Rotation(1.0, wires=0)
qml.expval(qml.X(0))
with pytest.raises(ValueError, match="unknown gradient method"):
_grad_method(tape, 0)
def test_probability(self):
"""Probability is the expectation value of a
higher order observable, and thus only supports numerical
differentiation"""
with qml.tape.JacobianTape() as tape:
qml.Rotation(0.543, wires=[0])
qml.Squeezing(0.543, 0, wires=[0])
qml.probs(wires=0)
assert _grad_method(tape, 0) == "F"
assert _grad_method(tape, 1) == "F"
assert _grad_method(tape, 2) == "F"
def test_finite_diff(self, monkeypatch):
"""If an op has grad_method=F, this should be respected
by the qml.tape.JacobianTape"""
monkeypatch.setattr(qml.Rotation, "grad_method", "F")
with qml.tape.JacobianTape() as tape:
qml.Rotation(0.543, wires=[0])
qml.Squeezing(0.543, 0, wires=[0])
qml.expval(qml.P(0))
assert _grad_method(tape, 0) == "F"
assert _grad_method(tape, 1) == "A"
assert _grad_method(tape, 2) == "A"
def test_independent(self):
"""Test that an independent variable is properly marked
as having a zero gradient"""
with qml.tape.JacobianTape() as tape:
qml.Rotation(0.543, wires=[0])
qml.Rotation(-0.654, wires=[1])
qml.expval(qml.P(0))
assert _grad_method(tape, 0) == "A"
assert _grad_method(tape, 1) == "0"
_gradient_analysis(tape)
assert tape._par_info[0]["grad_method"] == "A"
assert tape._par_info[1]["grad_method"] == "0"
def test_second_order_expectation(self):
"""Test that the expectation of a second-order observable forces
the gradient method to use the second-order parameter-shift rule"""
with qml.tape.JacobianTape() as tape:
qml.Rotation(1.0, wires=[0])
qml.expval(qml.NumberOperator(0)) # second order
assert _grad_method(tape, 0) == "A2"
def test_non_gaussian_operation(self):
"""Test that a non-Gaussian operation succeeding
a differentiable Gaussian operation results in
numeric differentiation."""
with qml.tape.JacobianTape() as tape:
qml.Rotation(1.0, wires=[0])
qml.Rotation(1.0, wires=[1])
# Non-Gaussian
qml.Kerr(1.0, wires=[1])
qml.expval(qml.P(0))
qml.expval(qml.X(1))
# First rotation gate has no succeeding non-Gaussian operation
assert _grad_method(tape, 0) == "A"
# Second rotation gate does no succeeding non-Gaussian operation
assert _grad_method(tape, 1) == "F"
# Kerr gate does not support the parameter-shift rule
assert _grad_method(tape, 2) == "F"
with qml.tape.JacobianTape() as tape:
qml.Rotation(1.0, wires=[0])
qml.Rotation(1.0, wires=[1])
# entangle the modes
qml.Beamsplitter(1.0, 0.0, wires=[0, 1])
# Non-Gaussian
qml.Kerr(1.0, wires=[1])
qml.expval(qml.P(0))
qml.expval(qml.X(1))
# After entangling the modes, the Kerr gate now succeeds
# both initial rotations
assert _grad_method(tape, 0) == "F"
assert _grad_method(tape, 1) == "F"
assert _grad_method(tape, 2) == "F"
def test_variance(self):
"""If the variance of the observable is first order, then
parameter-shift is supported. If the observable is second order,
however, only finite-differences is supported."""
with qml.tape.JacobianTape() as tape:
qml.Rotation(1.0, wires=[0])
qml.var(qml.P(0)) # first order
assert _grad_method(tape, 0) == "A"
with qml.tape.JacobianTape() as tape:
qml.Rotation(1.0, wires=[0])
qml.var(qml.NumberOperator(0)) # second order
assert _grad_method(tape, 0) == "F"
with qml.tape.JacobianTape() as tape:
qml.Rotation(1.0, wires=[0])
qml.Rotation(1.0, wires=[1])
qml.Beamsplitter(0.5, 0.0, wires=[0, 1])
qml.var(qml.NumberOperator(0)) # fourth order
qml.expval(qml.NumberOperator(1))
assert _grad_method(tape, 0) == "F"
assert _grad_method(tape, 1) == "F"
assert _grad_method(tape, 2) == "F"
assert _grad_method(tape, 3) == "F"