Merge pull request #167 from madcpf/board

Add one function into QuantumWorld

unitary/alpha/quantum_world.py

@@ -19,6 +19,8 @@
 from unitary.alpha.quantum_object import QuantumObject
 from unitary.alpha.sparse_vector_simulator import PostSelectOperation, SparseSimulator
 from unitary.alpha.qudit_state_transform import qudit_to_qubit_unitary, num_bits
+import numpy as np
+import itertools
 
 
 class QuantumWorld:
@@ -484,6 +486,36 @@ def get_histogram(
                 histogram[idx][cast(int, result[idx])] += 1
         return histogram
 
+    def get_correlated_histogram(
+        self, objects: Optional[Sequence[QuantumObject]] = None, count: int = 100
+    ) -> Dict[Tuple[int], int]:
+        """Creates histogram of the whole quantum world (or `objects` if specified)
+        based on measurements (peeks) carried out. Comparing to get_histogram(),
+        this statistics contains entanglement information accross quantum objects.
+
+        Parameters:
+            objects:    List of QuantumObjects
+            count:      Number of measurements
+
+        Returns:
+            A dictionary, with the keys being tuples representing each possible state of
+            the whole quantum world (or, if `objects` is specified, the key is a tuple of
+            the results of each object in `objects` and in the order of `objects`), and
+            the values being the count of that state.
+        """
+        if not objects:
+            objects = self.public_objects
+        peek_results = self.peek(objects=objects, convert_to_enum=False, count=count)
+        histogram = {}
+        for result in peek_results:
+            # Convert the list to tuple so that it could be the key of a dictionary.
+            key = tuple(result)
+            if key not in histogram:
+                histogram[key] = 1
+            else:
+                histogram[key] += 1
+        return histogram
+
     def get_probabilities(
         self, objects: Optional[Sequence[QuantumObject]] = None, count: int = 100
     ) -> List[Dict[int, float]]:

unitary/alpha/quantum_world_test.py

@@ -656,13 +656,17 @@ def test_get_histogram_and_get_probabilities_one_binary_qobject(
     )
     histogram = world.get_histogram()
     assert histogram == [{0: 0, 1: 100}]
+    histogram = world.get_correlated_histogram()
+    assert histogram == {(1,): 100}
     probs = world.get_probabilities()
     assert probs == [{0: 0.0, 1: 1.0}]
     bin_probs = world.get_binary_probabilities()
     assert bin_probs == [1.0]
     alpha.Flip()(l1)
     histogram = world.get_histogram()
     assert histogram == [{0: 100, 1: 0}]
+    histogram = world.get_correlated_histogram()
+    assert histogram == {(0,): 100}
     probs = world.get_probabilities()
     assert probs == [{0: 1.0, 1: 0.0}]
     bin_probs = world.get_binary_probabilities()
@@ -673,6 +677,10 @@ def test_get_histogram_and_get_probabilities_one_binary_qobject(
     assert len(histogram[0]) == 2
     assert histogram[0][0] > 10
     assert histogram[0][1] > 10
+    histogram = world.get_correlated_histogram()
+    assert len(histogram) == 2
+    assert histogram[(0,)] > 10
+    assert histogram[(1,)] > 10
     probs = world.get_probabilities()
     assert len(probs) == 1
     assert len(probs[0]) == 2
@@ -700,6 +708,8 @@ def test_get_histogram_and_get_probabilities_one_trinary_qobject(
     )
     histogram = world.get_histogram()
     assert histogram == [{0: 0, 1: 100, 2: 0}]
+    histogram = world.get_correlated_histogram()
+    assert histogram == {(1,): 100}
     probs = world.get_probabilities()
     assert probs == [{0: 0.0, 1: 1.0, 2: 0.0}]
     bin_probs = world.get_binary_probabilities()
@@ -723,13 +733,45 @@ def test_get_histogram_and_get_probabilities_two_qobjects(simulator, compile_to_
     )
     histogram = world.get_histogram()
     assert histogram == [{0: 0, 1: 100}, {0: 0, 1: 100, 2: 0}]
+    histogram = world.get_correlated_histogram()
+    assert histogram == {(1, 1): 100}
     probs = world.get_probabilities()
     assert probs == [{0: 0.0, 1: 1.0}, {0: 0.0, 1: 1.0, 2: 0.0}]
     bin_probs = world.get_binary_probabilities()
     assert bin_probs == [1.0, 1.0]
     histogram = world.get_histogram(objects=[l2], count=1000)
     assert histogram == [{0: 0, 1: 1000, 2: 0}]
+    histogram = world.get_correlated_histogram(objects=[l2], count=1000)
+    assert histogram == {(1,): 1000}
     probs = world.get_probabilities(objects=[l2], count=1000)
     assert probs == [{0: 0.0, 1: 1.0, 2: 0.0}]
     bin_probs = world.get_binary_probabilities(objects=[l2], count=1000)
     assert bin_probs == [1.0]
+
+
+@pytest.mark.parametrize(
+    ("simulator", "compile_to_qubits"),
+    [
+        (cirq.Simulator, False),
+        (cirq.Simulator, True),
+        # Cannot use SparseSimulator without `compile_to_qubits` due to issue #78.
+        (alpha.SparseSimulator, True),
+    ],
+)
+def test_get_correlated_histogram_with_entangled_qobjects(simulator, compile_to_qubits):
+    light1 = alpha.QuantumObject("l1", Light.GREEN)
+    light2 = alpha.QuantumObject("l2", Light.RED)
+    light3 = alpha.QuantumObject("l3", Light.RED)
+    light4 = alpha.QuantumObject("l4", Light.GREEN)
+    light5 = alpha.QuantumObject("l5", Light.RED)
+
+    world = alpha.QuantumWorld(
+        [light1, light2, light3, light4, light5],
+        sampler=simulator(),
+        compile_to_qubits=compile_to_qubits,
+    )
+    alpha.Split()(light1, light2, light3)
+    alpha.quantum_if(light2).equals(1).apply(alpha.Move())(light4, light5)
+
+    histogram = world.get_correlated_histogram()
+    assert histogram.keys() == {(0, 0, 1, 1, 0), (0, 1, 0, 0, 1)}