🐛 fix and streamline gate implementations

Signed-off-by: burgholzer <[email protected]>

src/mqt/qudits/quantum_circuit/gates/csum.py

@@ -38,24 +38,17 @@ def __array__(self) -> np.ndarray:
         ctrl_size = self.parent_circuit.dimensions[self._target_qudits[0]]
         target_size = self.parent_circuit.dimensions[self._target_qudits[1]]
 
-        matrix = np.zeros(ctrl_size * target_size, dtype="complex")
-
-        x_gate = X(self.parent_circuit, None, self._target_qudits[1], target_size, None)
-
+        x_gate = X(self.parent_circuit, "x", self._target_qudits[1], target_size, None)
+        x_mat = x_gate.to_matrix(identities=0)
+        matrix = np.zeros((ctrl_size * target_size, ctrl_size * target_size), dtype="complex")
         for i in range(ctrl_size):
-            temp = np.zeros(ctrl_size, dtype="complex")
-            mapmat = temp + np.outer(
-                np.array(from_dirac_to_basis([i], ctrl_size)), np.array(from_dirac_to_basis([i], ctrl_size))
-            )
-
-            Xmat = x_gate.to_matrix(identities=0)
-            Xmat_i = np.linalg.matrix_power(Xmat, i)
-
+            basis = np.array(from_dirac_to_basis([i], ctrl_size), dtype="complex")
+            mapmat = np.outer(basis, basis)
+            x_mat_i = np.linalg.matrix_power(x_mat, i)
             if self._target_qudits[0] < self._target_qudits[1]:
-                matrix = matrix + np.kron(mapmat, Xmat_i)
+                matrix += np.kron(mapmat, x_mat_i)
             else:
-                matrix = matrix + np.kron(Xmat_i, mapmat)
-
+                matrix += np.kron(x_mat_i, mapmat)
         return matrix
 
     def validate_parameter(self, parameter=None) -> bool:

src/mqt/qudits/quantum_circuit/gates/h.py

@@ -33,30 +33,17 @@ def __init__(
         self.qasm_tag = "h"
 
     def __array__(self) -> np.ndarray:
-        basis_states_projectors = [list(range(self._dimensions)), list(range(self._dimensions))]
-
-        matrix_array = np.outer([0 for x in range(self._dimensions)], [0 for x in range(self._dimensions)])
-        matrix = None
-
-        for e0, e1 in itertools.product(*basis_states_projectors):
+        matrix = np.zeros((self._dimensions, self._dimensions), dtype="complex")
+        for e0, e1 in itertools.product(range(self._dimensions), repeat=2):
             omega = np.mod(2 / self._dimensions * (e0 * e1), 2)
             omega = omega * np.pi * 1j
             omega = np.e**omega
-
-            l1 = [0 for x in range(self._dimensions)]
-            l2 = [0 for x in range(self._dimensions)]
-            l1[e0] = 1
-            l2[e1] = 1
-
-            array1 = np.array(l1, dtype="complex")
-            array2 = np.array(l2, dtype="complex")
-
-            result = omega * np.outer(array1, array2)
-
-            matrix_array = matrix_array + result
-            matrix = (1 / np.sqrt(self._dimensions)) * matrix_array
-
-        return matrix
+            array0 = np.zeros(self._dimensions, dtype="complex")
+            array1 = np.zeros(self._dimensions, dtype="complex")
+            array0[e0] = 1
+            array1[e1] = 1
+            matrix += omega * np.outer(array0, array1)
+        return matrix * (1 / np.sqrt(self._dimensions))
 
     def validate_parameter(self, parameter=None) -> bool:
         return True

src/mqt/qudits/quantum_circuit/gates/s.py

@@ -32,28 +32,16 @@ def __init__(
         self.qasm_tag = "s"
 
     def __array__(self) -> np.ndarray:
-        dimension = self._dimensions
-        levels_list = list(range(dimension))
-        if dimension == 2:
+        if self._dimensions == 2:
             return np.array([[1, 0], [0, 1j]])
-        matrix = np.outer([0 for x in range(dimension)], [0 for x in range(dimension)])
-
-        for lev in levels_list:
-            omega = np.e ** (2 * np.pi * 1j / dimension)
-            omega **= np.mod(lev * (lev + 1) / 2, dimension)
-
-            l1 = [0 for _ in range(dimension)]
-            l2 = [0 for _ in range(dimension)]
-            l1[lev] = 1
-            l2[lev] = 1
-
-            array1 = np.array(l1, dtype="complex")
-            array2 = np.array(l2, dtype="complex")
-
-            result = omega * np.outer(array1, array2)
-
-            matrix = matrix + result
-
+        matrix = np.zeros((self._dimensions, self._dimensions), dtype="complex")
+        for i in range(self._dimensions):
+            omega = np.e ** (2 * np.pi * 1j / self._dimensions)
+            omega **= np.mod(i * (i + 1) / 2, self._dimensions)
+            array = np.zeros(self._dimensions, dtype="complex")
+            array[i] = 1
+            result = omega * np.outer(array, array)
+            matrix += result
         return matrix
 
     def validate_parameter(self, parameter=None) -> bool:

src/mqt/qudits/quantum_circuit/gates/x.py

@@ -32,24 +32,14 @@ def __init__(
         self.qasm_tag = "x"
 
     def __array__(self) -> np.ndarray:
-        basis_states_list = list(range(self._dimensions))
-
-        matrix = np.outer([0 for x in range(self._dimensions)], [0 for x in range(self._dimensions)])
-
-        for i in basis_states_list:
+        matrix = np.zeros((self._dimensions, self._dimensions), dtype="complex")
+        for i in range(self._dimensions):
             i_plus_1 = np.mod(i + 1, self._dimensions)
-
-            l1 = [0 for x in range(self._dimensions)]
-            l2 = [0 for x in range(self._dimensions)]
-            l1[i_plus_1] = 1
-            l2[i] = 1
-
-            array1 = np.array(l1, dtype="complex")
-            array2 = np.array(l2, dtype="complex")
-
-            result = np.outer(array1, array2)
-            matrix = matrix + result
-
+            array1 = np.zeros(self._dimensions, dtype="complex")
+            array2 = np.zeros(self._dimensions, dtype="complex")
+            array1[i_plus_1] = 1
+            array2[i] = 1
+            matrix += np.outer(array1, array2)
         return matrix
 
     def validate_parameter(self, parameter=None) -> bool:

src/mqt/qudits/quantum_circuit/gates/z.py

@@ -32,27 +32,15 @@ def __init__(
         self.qasm_tag = "z"
 
     def __array__(self) -> np.ndarray:
-        dimension = self._dimensions
-        levels_list = list(range(dimension))
-
-        matrix = np.outer([0 for x in range(dimension)], [0 for x in range(dimension)])
-
-        for level in levels_list:
-            omega = np.mod(2 * level / dimension, 2)
+        matrix = np.zeros((self._dimensions, self._dimensions), dtype="complex")
+        for i in range(self._dimensions):
+            omega = np.mod(2 * i / self._dimensions, 2)
             omega = omega * np.pi * 1j
             omega = np.e**omega
-
-            l1 = [0 for _ in range(dimension)]
-            l2 = [0 for _ in range(dimension)]
-            l1[level] = 1
-            l2[level] = 1
-
-            array1 = np.array(l1, dtype="complex")
-            array2 = np.array(l2, dtype="complex")
-            proj = np.outer(array1, array2)
-            result = omega * proj
-
-            matrix = matrix + result
+            array = np.zeros(self._dimensions, dtype="complex")
+            array[i] = 1
+            result = omega * np.outer(array, array)
+            matrix += result
 
         return matrix