Merge pull request #1208 from qiboteam/tensorflow

Addition of parametrized gates missing in `TensorflowMatrices`
qiboteam · Feb 12, 2024 · 2a493f6 · 2a493f6
2 parents 45e4e22 + 85f26bc
commit 2a493f6
Showing 1 changed file with 120 additions and 0 deletions.
diff --git a/src/qibo/backends/tensorflow.py b/src/qibo/backends/tensorflow.py
@@ -34,6 +34,16 @@ def RZ(self, theta):
         phase = self.np.exp(0.5j * theta)
         return self.tf.cast([[self.np.conj(phase), 0], [0, phase]], dtype=self.dtype)
 
+    def GPI(self, phi):
+        phase = self.np.exp(1.0j * phi)
+        return self.tf.cast([[0, self.np.conj(phase)], [phase, 0]], dtype=self.dtype)
+
+    def GPI2(self, phi):
+        phase = self.np.exp(1.0j * phi)
+        return self.tf.cast(
+            [[1, -1.0j * self.np.conj(phase)], [-1.0j * phase, 1]], dtype=self.dtype
+        ) / self.np.sqrt(2)
+
     def U1(self, theta):
         phase = self.np.exp(1j * theta)
         return self.tf.cast([[1, 0], [0, phase]], dtype=self.dtype)
@@ -59,6 +69,9 @@ def U3(self, theta, phi, lam):
             dtype=self.dtype,
         )
 
+    def U1q(self, theta, phi):
+        return self.U3(theta, phi - self.np.pi / 2, self.np.pi / 2 - phi)
+
     def CRX(self, theta):
         r = self.RX(theta)
         return self.tf.cast(
@@ -157,6 +170,113 @@ def GeneralizedfSim(self, u, phi):
             dtype=self.dtype,
         )
 
+    def RXX(self, theta):
+        cos = self.np.cos(theta / 2.0) + 0j
+        isin = -1j * self.np.sin(theta / 2.0)
+        return self.tf.cast(
+            [
+                [cos, 0, 0, isin],
+                [0, cos, isin, 0],
+                [0, isin, cos, 0],
+                [isin, 0, 0, cos],
+            ],
+            dtype=self.dtype,
+        )
+
+    def RYY(self, theta):
+        cos = self.np.cos(theta / 2.0) + 0j
+        isin = -1j * self.np.sin(theta / 2.0)
+        return self.tf.cast(
+            [
+                [cos, 0, 0, -isin],
+                [0, cos, isin, 0],
+                [0, isin, cos, 0],
+                [-isin, 0, 0, cos],
+            ],
+            dtype=self.dtype,
+        )
+
+    def RZZ(self, theta):
+        phase = self.np.exp(0.5j * theta)
+        return self.tf.cast(
+            [
+                [self.np.conj(phase), 0, 0, 0],
+                [0, phase, 0, 0],
+                [0, 0, phase, 0],
+                [0, 0, 0, self.np.conj(phase)],
+            ],
+            dtype=self.dtype,
+        )
+
+    def RZX(self, theta):
+        cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j
+        return self.tf.cast(
+            [
+                [cos, -1j * sin, 0, 0],
+                [-1j * sin, cos, 0, 0],
+                [0, 0, cos, 1j * sin],
+                [0, 0, 1j * sin, cos],
+            ],
+            dtype=self.dtype,
+        )
+
+    def RXXYY(self, theta):
+        cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j
+        return self.tf.cast(
+            [
+                [1, 0, 0, 0],
+                [0, cos, -1j * sin, 0],
+                [0, -1j * sin, cos, 0],
+                [0, 0, 0, 1],
+            ],
+            dtype=self.dtype,
+        )
+
+    def MS(self, phi0, phi1, theta):
+        plus = self.np.exp(1.0j * (phi0 + phi1))
+        minus = self.np.exp(1.0j * (phi0 - phi1))
+        cos, sin = self.np.cos(theta / 2) + 0j, self.np.sin(theta / 2) + 0j
+        return self.tf.cast(
+            [
+                [cos, 0, 0, -1.0j * self.np.conj(plus) * sin],
+                [0, cos, -1.0j * self.np.conj(minus) * sin, 0],
+                [0, -1.0j * minus * sin, cos, 0],
+                [-1.0j * plus * sin, 0, 0, cos],
+            ],
+            dtype=self.dtype,
+        )
+
+    def GIVENS(self, theta):
+        return self.tf.cast(
+            [
+                [1, 0, 0, 0],
+                [0, self.np.cos(theta), -self.np.sin(theta), 0],
+                [0, self.np.sin(theta), self.np.cos(theta), 0],
+                [0, 0, 0, 1],
+            ],
+            dtype=self.dtype,
+        )
+
+    def RBS(self, theta):
+        return self.GIVENS(-theta)
+
+    def DEUTSCH(self, theta):
+        sin = self.np.sin(theta) + 0j  # 0j necessary for right tensorflow dtype
+        cos = self.np.cos(theta) + 0j
+        return self.tf.cast(
+            [
+                [1, 0, 0, 0, 0, 0, 0, 0],
+                [0, 1, 0, 0, 0, 0, 0, 0],
+                [0, 0, 1, 0, 0, 0, 0, 0],
+                [0, 0, 0, 1, 0, 0, 0, 0],
+                [0, 0, 0, 0, 1, 0, 0, 0],
+                [0, 0, 0, 0, 0, 1, 0, 0],
+                [0, 0, 0, 0, 0, 0, 1j * cos, sin],
+                [0, 0, 0, 0, 0, 0, sin, 1j * cos],
+            ],
+            dtype=self.dtype,
+        )
+
     def Unitary(self, u):
         return self.tf.cast(u, dtype=self.dtype)