def test_to_dm():
"""Tests the `to_dm` method that converts kets and bras to density matrices"""
dm0 = jnp.array(
[[1.0 + 0.0j, 0.0 + 0.0j], [0.0 + 0.0j, 0.0 + 0.0j]], dtype=jnp.complex64
)
dm1 = jnp.array(
[[0.0 + 0.0j, 0.0 + 0.0j], [0.0 + 0.0j, 1.0 + 0.0j]], dtype=jnp.complex64
)
# testing kets
assert_array_equal(to_dm(basis(2, 0)), dm0)
assert_array_equal(to_dm(basis(2, 1)), dm1)
# testing bras
assert_array_equal(to_dm(dag(basis(2, 0))), dm0)
assert_array_equal(to_dm(dag(basis(2, 1))), dm1)
def test_isdm():
# Check when matrix is non-semi-positive-definite
non_spd = jnp.array([[1, 1], [-1, 1]])
assert isdm(non_spd) == False
# Check standard density matrices
assert isdm(to_dm(basis(2, 0))) == True
# Check when matrix is non-hermitian
assert isdm(sigmax() * sigmay()) == False
# Check when trace is non-unity
assert isdm(jnp.eye(2) * 2) == False
def snap(hilbert_size, thetas):
"""
Constructs the matrix for a SNAP gate operation
that can be applied to a state.
Args:
hilbert_size (int): Hilbert space cuttoff
thetas (:obj:`jnp.ndarray`): A vector of theta values to
apply SNAP operation
Returns:
:obj:`jnp.ndarray`: matrix representing the SNAP gate
"""
op = 0 * jnp.eye(hilbert_size)
for i, theta in enumerate(thetas):
op += jnp.exp(1j * theta) * to_dm(basis(hilbert_size, i))
return op