def test_expect_sigmaxyz(op, state):
"""Tests the `expect` function on Pauli-X, Pauli-Y and Pauli-Z."""
# The stacked pytest decorators check all the argument combinations like a Cartesian product
if jnp.all(op != sigmaz()):
assert expect(op, state) == 0.0
elif jnp.all(state == basis(2, 0)):
assert expect(op, state) == 1.0
else:
assert expect(op, state) == -1.0
def test_expect_dag(oper, state):
r"""Reconciles the expectation value of a random operator with the analytic calculation
.. math:: <A> = <\psi|A|\psi>
"""
expected = jnp.dot(jnp.dot(dag(state), oper), state)
assert abs(expect(oper, state) - expected) < 1e-6
def cost(params, op):
"""Cost function to optimize
Args:
params (list): rotation angles for
x, y, and z rotations respectively
op (:obj:`jnp.ndarray`): Operator
with respect to which the expectation
value is to be calculated
Returns:
float: Expectation value of the evloved
state w.r.t the given operator `op`
"""
state = circuit(params)
return jnp.real(expect(op, state))
def test_coherent():
"""Tests the coherent state method"""
assert abs(expect(destroy(10), coherent(10, 0.5)) - 0.5) < 1e-4
def test_expect_herm(oper, state):
"""Tests that the expectation value of a hermitian operator is real and that of
the non-hermitian operator is complex"""
assert jnp.imag(expect(oper, state)) == 0.0
def test_coherent():
"""Tests the coherent state method"""
assert abs(expect(destroy(10), coherent(10, 0.5)) - 0.5) < 1e-4
# Tests the border case with alpha = 0
for N in range(2, 30, 5):
assert_array_almost_equal(coherent(N, 0), basis(N, 0))
def cost(params, op):
state = circuit(params)
return jnp.real(expect(op, state))
