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XanaduAI · Oct 17, 2024 · b161715 · b161715
1 parent 1f44cbc
commit b161715
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Showing 2 changed files with 27 additions and 24 deletions.
diff --git a/mrmustard/lab_dev/transformations/grn.py b/mrmustard/lab_dev/transformations/grn.py
@@ -34,22 +34,17 @@ class GRN(Channel):
     """
 
     short_name = "GRN"
+
     def __init__(
         self,
         modes: Sequence[int],
         Y: RealMatrix,
-        Y_train: bool = False,):
+        Y_train: bool = False,
+    ):
 
         super().__init__(modes_out=modes, modes_in=modes, name="GRN")
-        self._add_parameter(
-            make_parameter(
-                Y_train,
-                value= Y,
-                name="Y",
-                bounds = (None, None)
-            )
-        )
+        self._add_parameter(make_parameter(Y_train, value=Y, name="Y", bounds=(None, None)))
 
         self._representation = Bargmann.from_function(
-            fn=triples.gaussian_random_noise_Abc, Y = self.Y.value
+            fn=triples.gaussian_random_noise_Abc, Y=self.Y.value
         )
diff --git a/mrmustard/physics/triples.py b/mrmustard/physics/triples.py
@@ -606,21 +606,29 @@ def fock_damping_Abc(
 
 
 def gaussian_random_noise_Abc(Y: RealMatrix) -> Union[Matrix, Vector, Scalar]:
-    m = Y.shape[-1]//2
-    xi = math.eye(2*m) + Y/settings.HBAR
+    m = Y.shape[-1] // 2
+    xi = math.eye(2 * m) + Y / settings.HBAR
     xi_inv = math.inv(xi)
-    temp = math.block([[math.eye(2*m) - xi_inv, xi_inv],
-                       [xi_inv, math.eye(2*m) - xi_inv]])
-    R = 1/np.sqrt(2) * math.block([[math.eye(m), 1j * math.eye(m), math.zeros((m,2*m))],
-                                   [math.zeros((m,2*m)), math.eye(m), -1j * math.eye(m)],
-                                   [math.eye(m), -1j * math.eye(m), math.zeros((m,2*m))],
-                                   [math.zeros((m,2*m)), math.eye(m), 1j * math.eye(m)]])
-
-    A = math.Xmat(2*m) @ R @ temp @ math.conj(R).T
-    b = math.zeros(2*m)
-    c = 1/math.sqrt(math.det(xi))
-
-    return A,b,c
+    temp = math.block([[math.eye(2 * m) - xi_inv, xi_inv], [xi_inv, math.eye(2 * m) - xi_inv]])
+    R = (
+        1
+        / np.sqrt(2)
+        * math.block(
+            [
+                [math.eye(m), 1j * math.eye(m), math.zeros((m, 2 * m))],
+                [math.zeros((m, 2 * m)), math.eye(m), -1j * math.eye(m)],
+                [math.eye(m), -1j * math.eye(m), math.zeros((m, 2 * m))],
+                [math.zeros((m, 2 * m)), math.eye(m), 1j * math.eye(m)],
+            ]
+        )
+    )
+
+    A = math.Xmat(2 * m) @ R @ temp @ math.conj(R).T
+    b = math.zeros(2 * m)
+    c = 1 / math.sqrt(math.det(xi))
+
+    return A, b, c
+
 
 def bargmann_to_quadrature_Abc(n_modes: int, phi: float) -> tuple[Matrix, Vector, Scalar]:
     r"""