Reformatted

PennyLaneAI · May 7, 2024 · 998d21d · 998d21d
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commit 998d21d
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diff --git a/pennylane/ops/qutrit/channel.py b/pennylane/ops/qutrit/channel.py
@@ -134,6 +134,7 @@ class QutritDepolarizingChannel(Channel):
         wires (Sequence[int] or int): the wire the channel acts on
         id (str or None): String representing the operation (optional)
     """
+
     num_params = 1
     num_wires = 1
     grad_method = "F"
@@ -144,47 +145,47 @@ def __init__(self, p, wires, id=None):
     @staticmethod
     def compute_kraus_matrices(p):  # pylint:disable=arguments-differ
         r"""Kraus matrices representing the depolarizing channel.
-        Args:
-            p (float): each gate is applied with probability :math:`\frac{p}{9}`
-        Returns:
-            list (array): list of Kraus matrices
-        **Example**
-        >>> np.round(qml.QutritDepolarizingChannel.compute_kraus_matrices(0.5), 3)
-        array([[[ 0.745+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
-        [ 0.   +0.j   ,  0.745+0.j   ,  0.   +0.j   ],
-        [ 0.   +0.j   ,  0.   +0.j   ,  0.745+0.j   ]],
-
-       [[ 0.   +0.j   ,  0.236+0.j   ,  0.   +0.j   ],
-        [ 0.   +0.j   ,  0.   +0.j   ,  0.236+0.j   ],
-        [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ]],
-
-       [[ 0.   +0.j   ,  0.   +0.j   ,  0.236+0.j   ],
-        [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
-        [ 0.   +0.j   ,  0.236+0.j   ,  0.   +0.j   ]],
-
-       [[ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
-        [ 0.   +0.j   , -0.118+0.204j,  0.   +0.j   ],
-        [ 0.   +0.j   ,  0.   +0.j   , -0.118-0.204j]],
-
-       [[ 0.   +0.j   , -0.118+0.204j,  0.   +0.j   ],
-        [ 0.   +0.j   ,  0.   +0.j   , -0.118-0.204j],
-        [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ]],
-
-       [[ 0.   +0.j   ,  0.   +0.j   , -0.118-0.204j],
-        [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
-        [ 0.   +0.j   , -0.118+0.204j,  0.   +0.j   ]],
-
-       [[ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
-        [ 0.   +0.j   , -0.118-0.204j,  0.   +0.j   ],
-        [ 0.   +0.j   ,  0.   +0.j   , -0.118+0.204j]],
-
-       [[ 0.   +0.j   , -0.118-0.204j,  0.   +0.j   ],
-        [ 0.   +0.j   ,  0.   +0.j   , -0.118+0.204j],
-        [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ]],
-
-       [[ 0.   +0.j   ,  0.   +0.j   , -0.118+0.204j],
-        [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
-        [ 0.   +0.j   , -0.118-0.204j,  0.   +0.j   ]]])
+         Args:
+             p (float): each gate is applied with probability :math:`\frac{p}{9}`
+         Returns:
+             list (array): list of Kraus matrices
+         **Example**
+         >>> np.round(qml.QutritDepolarizingChannel.compute_kraus_matrices(0.5), 3)
+         array([[[ 0.745+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
+         [ 0.   +0.j   ,  0.745+0.j   ,  0.   +0.j   ],
+         [ 0.   +0.j   ,  0.   +0.j   ,  0.745+0.j   ]],
+
+        [[ 0.   +0.j   ,  0.236+0.j   ,  0.   +0.j   ],
+         [ 0.   +0.j   ,  0.   +0.j   ,  0.236+0.j   ],
+         [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ]],
+
+        [[ 0.   +0.j   ,  0.   +0.j   ,  0.236+0.j   ],
+         [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
+         [ 0.   +0.j   ,  0.236+0.j   ,  0.   +0.j   ]],
+
+        [[ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
+         [ 0.   +0.j   , -0.118+0.204j,  0.   +0.j   ],
+         [ 0.   +0.j   ,  0.   +0.j   , -0.118-0.204j]],
+
+        [[ 0.   +0.j   , -0.118+0.204j,  0.   +0.j   ],
+         [ 0.   +0.j   ,  0.   +0.j   , -0.118-0.204j],
+         [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ]],
+
+        [[ 0.   +0.j   ,  0.   +0.j   , -0.118-0.204j],
+         [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
+         [ 0.   +0.j   , -0.118+0.204j,  0.   +0.j   ]],
+
+        [[ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
+         [ 0.   +0.j   , -0.118-0.204j,  0.   +0.j   ],
+         [ 0.   +0.j   ,  0.   +0.j   , -0.118+0.204j]],
+
+        [[ 0.   +0.j   , -0.118-0.204j,  0.   +0.j   ],
+         [ 0.   +0.j   ,  0.   +0.j   , -0.118+0.204j],
+         [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ]],
+
+        [[ 0.   +0.j   ,  0.   +0.j   , -0.118+0.204j],
+         [ 0.236+0.j   ,  0.   +0.j   ,  0.   +0.j   ],
+         [ 0.   +0.j   , -0.118-0.204j,  0.   +0.j   ]]])
         """
         if not math.is_abstract(p) and not 0.0 <= p <= 1.0:
             raise ValueError("p must be in the interval [0,1]")
@@ -202,17 +203,17 @@ def compute_kraus_matrices(p):  # pylint:disable=arguments-differ
         depolarizing_mats = [
             [[z, one, z], [z, z, one], [one, z, z]],
             [[z, z, one], [one, z, z], [z, one, z]],
-
-            [[one, z, z], [z, w, z], [z, z, w ** 2]],
+            [[one, z, z], [z, w, z], [z, z, w**2]],
             [[z, w, 0j], [z, z, w**2], [one, z, z]],
             [[z, z, w**2], [one, z, z], [z, w, z]],
-
-            [[one, z, z], [z, w ** 2, z], [z, z, w ** 4]],
-            [[z, w ** 2, z], [z, z, w ** 4], [one, z, z]],
-            [[z, z, w**4], [one, z, z], [z, w**2, z]]
+            [[one, z, z], [z, w**2, z], [z, z, w**4]],
+            [[z, w**2, z], [z, z, w**4], [one, z, z]],
+            [[z, z, w**4], [one, z, z], [z, w**2, z]],
         ]
         normalization = math.sqrt(p / 9 + math.eps)
         Ks = [normalization * math.array(m, like=interface) for m in depolarizing_mats]
-        identity = math.sqrt(1 - (8 * p / 9) + math.eps) * math.array(math.eye(QUDIT_DIM, dtype=complex), like=interface)
+        identity = math.sqrt(1 - (8 * p / 9) + math.eps) * math.array(
+            math.eye(QUDIT_DIM, dtype=complex), like=interface
+        )
 
         return [identity] + Ks
diff --git a/tests/ops/qutrit/test_qutrit_channel_ops.py b/tests/ops/qutrit/test_qutrit_channel_ops.py
@@ -32,8 +32,8 @@ def get_expected_kraus_matrices(p):
         w = np.exp(2j * np.pi / 3)
 
         Z0 = np.eye(QUDIT_DIM)
-        Z1 = np.diag([1, w, w ** 2])
-        Z2 = np.diag([1, w ** 2, w ** 4])
+        Z1 = np.diag([1, w, w**2])
+        Z2 = np.diag([1, w**2, w**4])
 
         X0 = np.eye(QUDIT_DIM)
         X1 = np.array([[0, 1, 0], [0, 0, 1], [1, 0, 0]])
@@ -75,12 +75,16 @@ def test_grad_depolarizing(self, angle):
 
         @qml.qnode(dev)
         def circuit(p):
-            qml.TRX(angle, wires=0, subspace=(0,1))
-            qml.TRX(angle, wires=0, subspace=(1,2))
+            qml.TRX(angle, wires=0, subspace=(0, 1))
+            qml.TRX(angle, wires=0, subspace=(1, 2))
             qml.QutritDepolarizingChannel(p, wires=0)
             return qml.expval(qml.GellMann(0, 3) + qml.GellMann(0, 8))
 
-        expected_errorless = (np.sqrt(3)-3)*(1-np.cos(2*angle))/24 -2/np.sqrt(3)*np.sin(angle/2)**4+(np.sqrt(1/3)+1)*np.cos(angle/2)**2
+        expected_errorless = (
+            (np.sqrt(3) - 3) * (1 - np.cos(2 * angle)) / 24
+            - 2 / np.sqrt(3) * np.sin(angle / 2) ** 4
+            + (np.sqrt(1 / 3) + 1) * np.cos(angle / 2) ** 2
+        )
         assert np.allclose(circuit(prob), prob * expected_errorless)
 
         gradient = np.squeeze(qml.grad(circuit)(prob))
@@ -98,8 +102,8 @@ def expected_jac_fn(p):
         w = np.exp(2j * np.pi / 3)
 
         Z0 = np.eye(QUDIT_DIM)
-        Z1 = np.diag([1, w, w ** 2])
-        Z2 = np.diag([1, w ** 2, w ** 4])
+        Z1 = np.diag([1, w, w**2])
+        Z2 = np.diag([1, w**2, w**4])
 
         X0 = np.eye(QUDIT_DIM)
         X1 = np.array([[0, 1, 0], [0, 0, 1], [1, 0, 0]])
@@ -154,6 +158,7 @@ def test_kraus_jac_torch(self):
     def test_kraus_jac_tf(self):
         """Tests Jacobian of Kraus matrices using tensorflow."""
         import tensorflow as tf
+
         p = tf.Variable(0.43)
         with tf.GradientTape() as real_tape:
             real_out = self.kraus_fn_real(p)