todo: how to apply hadamard gates after entanglement

computer.py

@@ -29,15 +29,16 @@ class Qubit(list):
         return rv
 
 
-def measure(qubits):
+def measure(qubits, times=10):
     """
-    Measure result from computation
+    Measure result from computation based on the qubit population
     """
     probabilites = [q[0] ** 2 for q in qubits]
-    return bin(random.choices(
+    return [bin(m) for m in random.choices(
         population=range(len(qubits)),
-        weights=probabilites
-    )[0])
+        weights=probabilites,
+        k=times
+    )]
 
 
 _0 = Qubit([[1], [0]])
@@ -89,13 +90,23 @@ def main():
     assert CNOT * (_1 * _1) == (_1 * _0)
 
     # TEST HADAMARD
+    # Put two qubits in superposition
     superposition = Qubit(H * _0) * Qubit(H * _0)
     print(superposition)
-    CNOT_superposition = Qubit(CNOT * superposition)
-    print(CNOT_superposition)
+    # Entangle the qubits
+    entanglement = Qubit(CNOT * superposition)
+    print(entanglement)
 
-    print(measure(CNOT_superposition))
-    # print(INVERTED_CNOT)
+    # TODO: What does it mean to apply H gate on the entangled qubits???
+    #  https://en.wikipedia.org/wiki/Controlled_NOT_gate#Behaviour_in_the_Hadamard_transformed_basis
+    #  Should it be:
+    #  q1 = Qubit(H * entanglement[:2])
+    #  q2 = Qubit(H * entanglement[3:])
+    # /TODO
+
+    # this should get us 1/4 chance for each combination of 00 01 10 and 10;
+    # measure 42 times
+    print(measure(entanglement, times=42))
 
     # TEST MY MEMORY
     # rv = _0