Repository: Qiskit/qiskit (python)

Issue:
Improve docstring of plot_circuit_layout
### What should we add?

https://docs.quantum.ibm.com/api/qiskit/qiskit.visualization.plot_circuit_layout#qiskitvisualizationplot_circuit_layout

For example, the documentation of the `view` argument just says

>view (str): Layout view: either 'virtual' or 'physical'.

which is not informative.

Pull request description:
improve docstring of plot_circuit_layout
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### Summary

Fixes #12334

### Details and comments




Patch:
diff --git a/Cargo.lock b/Cargo.lock
index 33114124e..b6915167f 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -734,9 +734,9 @@ dependencies = [
 
 [[package]]
 name = "num-complex"
-version = "0.4.5"
+version = "0.4.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "23c6602fda94a57c990fe0df199a035d83576b496aa29f4e634a8ac6004e68a6"
+checksum = "73f88a1307638156682bada9d7604135552957b7818057dcef22705b4d509495"
 dependencies = [
  "bytemuck",
  "num-traits",
diff --git a/qiskit/quantum_info/states/stabilizerstate.py b/qiskit/quantum_info/states/stabilizerstate.py
index 7f616bcff..4ae16c32b 100644
--- a/qiskit/quantum_info/states/stabilizerstate.py
+++ b/qiskit/quantum_info/states/stabilizerstate.py
@@ -386,8 +386,17 @@ class StabilizerState(QuantumState):
 
         return probs
 
-    def probabilities_dict(self, qargs: None | list = None, decimals: None | int = None) -> dict:
-        """Return the subsystem measurement probability dictionary.
+    def probabilities_dict_from_bitstring(
+        self,
+        outcome_bitstring: str,
+        qargs: None | list = None,
+        decimals: None | int = None,
+    ) -> dict[str, float]:
+        """Return the subsystem measurement probability dictionary utilizing
+        a targeted outcome_bitstring to perform the measurement for. This
+        will calculate a probability for only a single targeted
+        outcome_bitstring value, giving a performance boost over calculating
+        all possible outcomes.
 
         Measurement probabilities are with respect to measurement in the
         computation (diagonal) basis.
@@ -398,30 +407,44 @@ class StabilizerState(QuantumState):
         inserted between integers so that subsystems can be distinguished.
 
         Args:
+            outcome_bitstring (None or str): targeted outcome bitstring
+                to perform a measurement calculation for, this will significantly
+                reduce the number of calculation performed (Default: None)
             qargs (None or list): subsystems to return probabilities for,
-                if None return for all subsystems (Default: None).
+                    if None return for all subsystems (Default: None).
             decimals (None or int): the number of decimal places to round
-                values. If None no rounding is done (Default: None).
+                    values. If None no rounding is done (Default: None)
 
         Returns:
-            dict: The measurement probabilities in dict (ket) form.
+            dict[str, float]: The measurement probabilities in dict (ket) form.
         """
-        if qargs is None:
-            qubits = range(self.clifford.num_qubits)
-        else:
-            qubits = qargs
+        return self._get_probabilities_dict(
+            outcome_bitstring=outcome_bitstring, qargs=qargs, decimals=decimals
+        )
 
-        outcome = ["X"] * len(qubits)
-        outcome_prob = 1.0
-        probs = {}  # probabilities dictionary
+    def probabilities_dict(
+        self, qargs: None | list = None, decimals: None | int = None
+    ) -> dict[str, float]:
+        """Return the subsystem measurement probability dictionary.
 
-        self._get_probabilities(qubits, outcome, outcome_prob, probs)
+        Measurement probabilities are with respect to measurement in the
+        computation (diagonal) basis.
 
-        if decimals is not None:
-            for key, value in probs.items():
-                probs[key] = round(value, decimals)
+        This dictionary representation uses a Ket-like notation where the
+        dictionary keys are qudit strings for the subsystem basis vectors.
+        If any subsystem has a dimension greater than 10 comma delimiters are
+        inserted between integers so that subsystems can be distinguished.
 
-        return probs
+        Args:
+            qargs (None or list): subsystems to return probabilities for,
+                if None return for all subsystems (Default: None).
+            decimals (None or int): the number of decimal places to round
+                values. If None no rounding is done (Default: None).
+
+        Returns:
+            dict: The measurement probabilities in dict (key) form.
+        """
+        return self._get_probabilities_dict(outcome_bitstring=None, qargs=qargs, decimals=decimals)
 
     def reset(self, qargs: list | None = None) -> StabilizerState:
         """Reset state or subsystems to the 0-state.
@@ -644,22 +667,48 @@ class StabilizerState(QuantumState):
     # -----------------------------------------------------------------------
     # Helper functions for calculating the probabilities
     # -----------------------------------------------------------------------
-    def _get_probabilities(self, qubits, outcome, outcome_prob, probs):
-        """Recursive helper function for calculating the probabilities"""
+    def _get_probabilities(
+        self,
+        qubits: range,
+        outcome: list[str],
+        outcome_prob: float,
+        probs: dict[str, float],
+        outcome_bitstring: str = None,
+    ):
+        """Recursive helper function for calculating the probabilities
 
-        qubit_for_branching = -1
-        ret = self.copy()
+        Args:
+            qubits (range): range of qubits
+            outcome (list[str]): outcome being built
+            outcome_prob (float): probabilitiy of the outcome
+            probs (dict[str, float]): holds the outcomes and probabilitiy results
+            outcome_bitstring (str): target outcome to measure which reduces measurements, None
+                if not targeting a specific target
+        """
+        qubit_for_branching: int = -1
 
+        ret: StabilizerState = self.copy()
+
+        # Find outcomes for each qubit
         for i in range(len(qubits)):
-            qubit = qubits[len(qubits) - i - 1]
             if outcome[i] == "X":
-                is_deterministic = not any(ret.clifford.stab_x[:, qubit])
-                if is_deterministic:
-                    single_qubit_outcome = ret._measure_and_update(qubit, 0)
-                    if single_qubit_outcome:
-                        outcome[i] = "1"
+                # Retrieve the qubit for the current measurement
+                qubit = qubits[(len(qubits) - i - 1)]
+                # Determine if the probabilitiy is deterministic
+                if not any(ret.clifford.stab_x[:, qubit]):
+                    single_qubit_outcome: np.int64 = ret._measure_and_update(qubit, 0)
+                    if outcome_bitstring is None or (
+                        int(outcome_bitstring[i]) == single_qubit_outcome
+                    ):
+                        # No outcome_bitstring target, or using outcome_bitstring target and
+                        # the single_qubit_outcome equals the desired outcome_bitstring target value,
+                        # then use current outcome_prob value
+                        outcome[i] = str(single_qubit_outcome)
                     else:
-                        outcome[i] = "0"
+                        # If the single_qubit_outcome does not equal the outcome_bitsring target
+                        # then we know that the probability will be 0
+                        outcome[i] = str(outcome_bitstring[i])
+                        outcome_prob = 0
                 else:
                     qubit_for_branching = i
 
@@ -668,15 +717,57 @@ class StabilizerState(QuantumState):
             probs[str_outcome] = outcome_prob
             return
 
-        for single_qubit_outcome in range(0, 2):
+        for single_qubit_outcome in (
+            range(0, 2)
+            if (outcome_bitstring is None)
+            else [int(outcome_bitstring[qubit_for_branching])]
+        ):
             new_outcome = outcome.copy()
-            if single_qubit_outcome:
-                new_outcome[qubit_for_branching] = "1"
-            else:
-                new_outcome[qubit_for_branching] = "0"
+            new_outcome[qubit_for_branching] = str(single_qubit_outcome)
 
             stab_cpy = ret.copy()
             stab_cpy._measure_and_update(
-                qubits[len(qubits) - qubit_for_branching - 1], single_qubit_outcome
+                qubits[(len(qubits) - qubit_for_branching - 1)], single_qubit_outcome
+            )
+            stab_cpy._get_probabilities(
+                qubits, new_outcome, (0.5 * outcome_prob), probs, outcome_bitstring
             )
-            stab_cpy._get_probabilities(qubits, new_outcome, 0.5 * outcome_prob, probs)
+
+    def _get_probabilities_dict(
+        self,
+        outcome_bitstring: None | str = None,
+        qargs: None | list = None,
+        decimals: None | int = None,
+    ) -> dict[str, float]:
+        """Helper Function for calculating the subsystem measurement probability dictionary.
+        When the targeted outcome_bitstring value is set, then only the single outcome_bitstring
+        probability will be calculated.
+
+        Args:
+            outcome_bitstring (None or str): targeted outcome bitstring
+                to perform a measurement calculation for, this will significantly
+                reduce the number of calculation performed (Default: None)
+            qargs (None or list): subsystems to return probabilities for,
+                if None return for all subsystems (Default: None).
+            decimals (None or int): the number of decimal places to round
+                values. If None no rounding is done (Default: None).
+
+        Returns:
+            dict: The measurement probabilities in dict (key) form.
+        """
+        if qargs is None:
+            qubits = range(self.clifford.num_qubits)
+        else:
+            qubits = qargs
+
+        outcome = ["X"] * len(qubits)
+        outcome_prob = 1.0
+        probs: dict[str, float] = {}  # Probabilities dict to return with the measured values
+
+        self._get_probabilities(qubits, outcome, outcome_prob, probs, outcome_bitstring)
+
+        if decimals is not None:
+            for key, value in probs.items():
+                probs[key] = round(value, decimals)
+
+        return probs
diff --git a/qiskit/visualization/gate_map.py b/qiskit/visualization/gate_map.py
index d8ffb6e10..c7cc0727a 100644
--- a/qiskit/visualization/gate_map.py
+++ b/qiskit/visualization/gate_map.py
@@ -1122,7 +1122,13 @@ def plot_circuit_layout(circuit, backend, view="virtual", qubit_coordinates=None
     Args:
         circuit (QuantumCircuit): Input quantum circuit.
         backend (Backend): Target backend.
-        view (str): Layout view: either 'virtual' or 'physical'.
+        view (str): How to label qubits in the layout. Options:
+
+          - ``"virtual"``: Label each qubit with the index of the virtual qubit that
+            mapped to it.
+          - ``"physical"``: Label each qubit with the index of the physical qubit that it
+            corresponds to on the device.
+
         qubit_coordinates (Sequence): An optional sequence input (list or array being the
             most common) of 2d coordinates for each qubit. The length of the
             sequence must match the number of qubits on the backend. The sequence
diff --git a/releasenotes/notes/outcome_bitstring_target_for_probabilities_dict-e53f524d115bbcfc.yaml b/releasenotes/notes/outcome_bitstring_target_for_probabilities_dict-e53f524d115bbcfc.yaml
new file mode 100644
index 000000000..73da8e6b7
--- /dev/null
+++ b/releasenotes/notes/outcome_bitstring_target_for_probabilities_dict-e53f524d115bbcfc.yaml
@@ -0,0 +1,13 @@
+---
+features:
+  - |
+    The :class:'.StabilizerState' class now has a new method 
+    :meth:'~.StabilizerState.probabilities_dict_from_bitstring' allowing the 
+    user to pass single bitstring to measure an outcome for. Previouslly the 
+    :meth:'~.StabilizerState.probabilities_dict' would be utilized and would 
+    at worst case calculate (2^n) number of probabilbity calculations (depending
+    on the state), even if a user wanted a single result. With this new method 
+    the user can calculate just the single outcome bitstring value a user passes 
+    to measure the probability for. As the number of qubits increases, the more 
+    prevelant the performance enhancement may be (depending on the state) as only 
+    1 bitstring result is measured.


Test patch:
diff --git a/test/python/quantum_info/states/test_stabilizerstate.py b/test/python/quantum_info/states/test_stabilizerstate.py
index 56fecafbe..4e1659ff6 100644
--- a/test/python/quantum_info/states/test_stabilizerstate.py
+++ b/test/python/quantum_info/states/test_stabilizerstate.py
@@ -13,6 +13,7 @@
 
 """Tests for Stabilizerstate quantum state class."""
 
+from itertools import product
 import unittest
 import logging
 from ddt import ddt, data, unpack
@@ -32,6 +33,61 @@ from test import QiskitTestCase  # pylint: disable=wrong-import-order
 logger = logging.getLogger(__name__)
 
 
+class StabilizerStateTestingTools:
+    """Test tools for verifying test cases in StabilizerState"""
+
+    @staticmethod
+    def _bitstring_product_dict(bitstring_length: int, skip_entries: dict = None) -> dict:
+        """Retrieves a dict of every possible product of '0', '1' for length bitstring_length
+        pass in a dict to use the keys as entries to skip adding to the dict
+
+        Args:
+            bitstring_length (int): length of the bitstring product
+            skip_entries (dict[str, float], optional): dict entries to skip adding to the dict based
+                on existing keys in the dict passed in. Defaults to {}.
+
+        Returns:
+            dict[str, float]: dict with entries, all set to 0
+        """
+        if skip_entries is None:
+            skip_entries = {}
+        return {
+            result: 0
+            for result in ["".join(x) for x in product(["0", "1"], repeat=bitstring_length)]
+            if result not in skip_entries
+        }
+
+    @staticmethod
+    def _verify_individual_bitstrings(
+        testcase: QiskitTestCase,
+        target_dict: dict,
+        stab: StabilizerState,
+        qargs: list = None,
+        decimals: int = None,
+        dict_almost_equal: bool = False,
+    ) -> None:
+        """Helper that iterates through the target_dict and checks all probabilities by
+        running the value through the probabilities_dict_from_bitstring method for
+        retrieving a single measurement
+
+        Args:
+            target_dict (dict[str, float]): dict to check probabilities for
+            stab (StabilizerState): stabilizerstate object to run probabilities_dict_from_bitstring on
+            qargs (None or list): subsystems to return probabilities for,
+                    if None return for all subsystems (Default: None).
+            decimals (None or int): the number of decimal places to round
+                    values. If None no rounding is done (Default: None)
+            dict_almost_equal (bool): utilize assertDictAlmostEqual when true, assertDictEqual when false
+        """
+        for outcome_bitstring in target_dict:
+            (testcase.assertDictAlmostEqual if (dict_almost_equal) else testcase.assertDictEqual)(
+                stab.probabilities_dict_from_bitstring(
+                    outcome_bitstring=outcome_bitstring, qargs=qargs, decimals=decimals
+                ),
+                {outcome_bitstring: target_dict[outcome_bitstring]},
+            )
+
+
 @ddt
 class TestStabilizerState(QiskitTestCase):
     """Tests for StabilizerState class."""
@@ -315,6 +371,8 @@ class TestStabilizerState(QiskitTestCase):
                 value = stab.probabilities_dict()
                 target = {"0": 1}
                 self.assertEqual(value, target)
+                target.update({"1": 0.0})
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab)
                 probs = stab.probabilities()
                 target = np.array([1, 0])
                 self.assertTrue(np.allclose(probs, target))
@@ -326,6 +384,8 @@ class TestStabilizerState(QiskitTestCase):
                 value = stab.probabilities_dict()
                 target = {"1": 1}
                 self.assertEqual(value, target)
+                target.update({"0": 0.0})
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab)
                 probs = stab.probabilities()
                 target = np.array([0, 1])
                 self.assertTrue(np.allclose(probs, target))
@@ -338,6 +398,7 @@ class TestStabilizerState(QiskitTestCase):
                 value = stab.probabilities_dict()
                 target = {"0": 0.5, "1": 0.5}
                 self.assertEqual(value, target)
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab)
                 probs = stab.probabilities()
                 target = np.array([0.5, 0.5])
                 self.assertTrue(np.allclose(probs, target))
@@ -355,43 +416,56 @@ class TestStabilizerState(QiskitTestCase):
                 value = stab.probabilities_dict()
                 target = {"00": 0.5, "01": 0.5}
                 self.assertEqual(value, target)
+                target.update({"10": 0.0, "11": 0.0})
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab)
                 probs = stab.probabilities()
                 target = np.array([0.5, 0.5, 0, 0])
                 self.assertTrue(np.allclose(probs, target))
 
+        qargs: list = [0, 1]
         for _ in range(self.samples):
             with self.subTest(msg="P([0, 1])"):
-                value = stab.probabilities_dict([0, 1])
+                value = stab.probabilities_dict(qargs)
                 target = {"00": 0.5, "01": 0.5}
                 self.assertEqual(value, target)
-                probs = stab.probabilities([0, 1])
+                target.update({"10": 0.0, "11": 0.0})
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab, qargs)
+                probs = stab.probabilities(qargs)
                 target = np.array([0.5, 0.5, 0, 0])
                 self.assertTrue(np.allclose(probs, target))
 
+        qargs: list = [1, 0]
         for _ in range(self.samples):
             with self.subTest(msg="P([1, 0])"):
-                value = stab.probabilities_dict([1, 0])
+                value = stab.probabilities_dict(qargs)
                 target = {"00": 0.5, "10": 0.5}
                 self.assertEqual(value, target)
-                probs = stab.probabilities([1, 0])
+                target.update({"01": 0.0, "11": 0.0})
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab, qargs)
+                probs = stab.probabilities(qargs)
                 target = np.array([0.5, 0, 0.5, 0])
                 self.assertTrue(np.allclose(probs, target))
 
+        qargs: list = [0]
         for _ in range(self.samples):
             with self.subTest(msg="P[0]"):
-                value = stab.probabilities_dict([0])
+                value = stab.probabilities_dict(qargs)
                 target = {"0": 0.5, "1": 0.5}
                 self.assertEqual(value, target)
-                probs = stab.probabilities([0])
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab, qargs)
+                probs = stab.probabilities(qargs)
                 target = np.array([0.5, 0.5])
                 self.assertTrue(np.allclose(probs, target))
 
+        qargs: list = [1]
         for _ in range(self.samples):
             with self.subTest(msg="P([1])"):
-                value = stab.probabilities_dict([1])
+                value = stab.probabilities_dict(qargs)
                 target = {"0": 1.0}
                 self.assertEqual(value, target)
-                probs = stab.probabilities([1])
+                target.update({"1": 0.0})
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab, qargs)
+                probs = stab.probabilities(qargs)
                 target = np.array([1, 0])
                 self.assertTrue(np.allclose(probs, target))
 
@@ -405,9 +479,10 @@ class TestStabilizerState(QiskitTestCase):
         qc.h(2)
         stab = StabilizerState(qc)
 
+        decimals: int = 1
         for _ in range(self.samples):
             with self.subTest(msg="P(None), decimals=1"):
-                value = stab.probabilities_dict(decimals=1)
+                value = stab.probabilities_dict(decimals=decimals)
                 target = {
                     "000": 0.1,
                     "001": 0.1,
@@ -419,13 +494,17 @@ class TestStabilizerState(QiskitTestCase):
                     "111": 0.1,
                 }
                 self.assertEqual(value, target)
-                probs = stab.probabilities(decimals=1)
+                StabilizerStateTestingTools._verify_individual_bitstrings(
+                    self, target, stab, decimals=decimals
+                )
+                probs = stab.probabilities(decimals=decimals)
                 target = np.array([0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1])
                 self.assertTrue(np.allclose(probs, target))
 
+        decimals: int = 2
         for _ in range(self.samples):
             with self.subTest(msg="P(None), decimals=2"):
-                value = stab.probabilities_dict(decimals=2)
+                value = stab.probabilities_dict(decimals=decimals)
                 target = {
                     "000": 0.12,
                     "001": 0.12,
@@ -437,13 +516,17 @@ class TestStabilizerState(QiskitTestCase):
                     "111": 0.12,
                 }
                 self.assertEqual(value, target)
-                probs = stab.probabilities(decimals=2)
+                StabilizerStateTestingTools._verify_individual_bitstrings(
+                    self, target, stab, decimals=decimals
+                )
+                probs = stab.probabilities(decimals=decimals)
                 target = np.array([0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 0.12])
                 self.assertTrue(np.allclose(probs, target))
 
+        decimals: int = 3
         for _ in range(self.samples):
             with self.subTest(msg="P(None), decimals=3"):
-                value = stab.probabilities_dict(decimals=3)
+                value = stab.probabilities_dict(decimals=decimals)
                 target = {
                     "000": 0.125,
                     "001": 0.125,
@@ -455,10 +538,72 @@ class TestStabilizerState(QiskitTestCase):
                     "111": 0.125,
                 }
                 self.assertEqual(value, target)
+                StabilizerStateTestingTools._verify_individual_bitstrings(
+                    self, target, stab, decimals=decimals
+                )
                 probs = stab.probabilities(decimals=3)
                 target = np.array([0.125, 0.125, 0.125, 0.125, 0.125, 0.125, 0.125, 0.125])
                 self.assertTrue(np.allclose(probs, target))
 
+    @combine(num_qubits=[5, 6, 7, 8, 9])
+    def test_probabilities_dict_from_bitstring(self, num_qubits):
+        """Test probabilities_dict_from_bitstring methods with medium number of qubits that are still
+        reasonable to calculate the full dict with probabilities_dict of all possible outcomes"""
+
+        qc: QuantumCircuit = QuantumCircuit(num_qubits)
+        for qubit_num in range(0, num_qubits):
+            qc.h(qubit_num)
+        stab = StabilizerState(qc)
+
+        expected_result: float = float(1 / (2**num_qubits))
+        target_dict: dict = StabilizerStateTestingTools._bitstring_product_dict(num_qubits)
+        target_dict.update((k, expected_result) for k in target_dict)
+
+        for _ in range(self.samples):
+            with self.subTest(msg="P(None)"):
+                value = stab.probabilities_dict()
+                self.assertDictEqual(value, target_dict)
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target_dict, stab)
+                probs = stab.probabilities()
+                target = np.array(([expected_result] * (2**num_qubits)))
+                self.assertTrue(np.allclose(probs, target))
+
+        # H gate at qubit 0, Every gate after is an X gate
+        # will result in 2 outcomes with 0.5
+        qc = QuantumCircuit(num_qubits)
+        qc.h(0)
+        for qubit_num in range(1, num_qubits):
+            qc.x(qubit_num)
+        stab = StabilizerState(qc)
+
+        # Build the 2 expected outcome bitstrings for
+        # 0.5 probability based on h and x gates
+        target_1: str = "".join(["1" * (num_qubits - 1)] + ["0"])
+        target_2: str = "".join(["1" * num_qubits])
+        target: dict = {target_1: 0.5, target_2: 0.5}
+        target_all_bitstrings: dict = StabilizerStateTestingTools._bitstring_product_dict(
+            num_qubits, target
+        )
+        target_all_bitstrings.update(target_all_bitstrings)
+
+        # Numpy Array to verify stab.probabilities()
+        target_np_dict: dict = StabilizerStateTestingTools._bitstring_product_dict(
+            num_qubits, [target_1, target_2]
+        )
+        target_np_dict.update(target)
+        target_np_array: np.ndarray = np.array(list(target_np_dict.values()))
+
+        for _ in range(self.samples):
+            with self.subTest(msg="P(None)"):
+                stab = StabilizerState(qc)
+                value = stab.probabilities_dict()
+                self.assertEqual(value, target)
+                StabilizerStateTestingTools._verify_individual_bitstrings(
+                    self, target_all_bitstrings, stab
+                )
+                probs = stab.probabilities()
+                self.assertTrue(np.allclose(probs, target_np_array))
+
     def test_probabilities_dict_ghz(self):
         """Test probabilities and probabilities_dict method of a subsystem of qubits"""
 
@@ -473,6 +618,8 @@ class TestStabilizerState(QiskitTestCase):
             value = stab.probabilities_dict()
             target = {"000": 0.5, "111": 0.5}
             self.assertEqual(value, target)
+            target.update(StabilizerStateTestingTools._bitstring_product_dict(num_qubits, target))
+            StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab)
             probs = stab.probabilities()
             target = np.array([0.5, 0, 0, 0, 0, 0, 0, 0.5])
             self.assertTrue(np.allclose(probs, target))
@@ -483,6 +630,10 @@ class TestStabilizerState(QiskitTestCase):
                 probs = stab.probabilities_dict(qargs)
                 target = {"000": 0.5, "111": 0.5}
                 self.assertDictAlmostEqual(probs, target)
+                target.update(
+                    StabilizerStateTestingTools._bitstring_product_dict(num_qubits, target)
+                )
+                StabilizerStateTestingTools._verify_individual_bitstrings(self, target, stab, qargs)
                 probs = stab.probabilities(qargs)
                 target = np.array([0.5, 0, 0, 0, 0, 0, 0, 0.5])
                 self.assertTrue(np.allclose(probs, target))
@@ -493,6 +644,10 @@ class TestStabilizerState(QiskitTestCase):
                 probs = stab.probabilities_dict(qargs)
                 target = {"00": 0.5, "11": 0.5}
                 self.assertDictAlmostEqual(probs, target)
+                target.update(StabilizerStateTestingTools._bitstring_product_dict(2, target))
+                StabilizerStateTestingTools._verify_individual_bitstrings(
+                    self, target, stab, qargs, dict_almost_equal=True
+                )
                 probs = stab.probabilities(qargs)
                 target = np.array([0.5, 0, 0, 0.5])
                 self.assertTrue(np.allclose(probs, target))
@@ -503,6 +658,9 @@ class TestStabilizerState(QiskitTestCase):
                 probs = stab.probabilities_dict(qargs)
                 target = {"0": 0.5, "1": 0.5}
                 self.assertDictAlmostEqual(probs, target)
+                StabilizerStateTestingTools._verify_individual_bitstrings(
+                    self, target, stab, qargs, dict_almost_equal=True
+                )
                 probs = stab.probabilities(qargs)
                 target = np.array([0.5, 0.5])
                 self.assertTrue(np.allclose(probs, target))
@@ -520,10 +678,17 @@ class TestStabilizerState(QiskitTestCase):
                 stab = StabilizerState(cliff)
                 probs = stab.probabilities(qargs)
                 probs_dict = stab.probabilities_dict(qargs)
+                StabilizerStateTestingTools._verify_individual_bitstrings(
+                    self, probs_dict, stab, qargs
+                )
                 target = Statevector(qc).probabilities(qargs)
                 target_dict = Statevector(qc).probabilities_dict(qargs)
+                Statevector(qc).probabilities_dict()
                 self.assertTrue(np.allclose(probs, target))
                 self.assertDictAlmostEqual(probs_dict, target_dict)
+                StabilizerStateTestingTools._verify_individual_bitstrings(
+                    self, target_dict, stab, qargs, dict_almost_equal=True
+                )
 
     @combine(num_qubits=[2, 3, 4, 5])
     def test_expval_from_random_clifford(self, num_qubits):
@@ -972,10 +1137,22 @@ class TestStabilizerStateExpectationValue(QiskitTestCase):
         # [XX, -ZZ] and [XX, YY] both generate the stabilizer group {II, XX, YY, -ZZ}
         self.assertTrue(cliff1.equiv(cliff2))
         self.assertEqual(cliff1.probabilities_dict(), cliff2.probabilities_dict())
+        StabilizerStateTestingTools._verify_individual_bitstrings(
+            self, cliff1.probabilities_dict(), cliff2
+        )
+        StabilizerStateTestingTools._verify_individual_bitstrings(
+            self, cliff2.probabilities_dict(), cliff1
+        )
 
         # [XX, ZZ] and [XX, -YY] both generate the stabilizer group {II, XX, -YY, ZZ}
         self.assertTrue(cliff3.equiv(cliff4))
         self.assertEqual(cliff3.probabilities_dict(), cliff4.probabilities_dict())
+        StabilizerStateTestingTools._verify_individual_bitstrings(
+            self, cliff3.probabilities_dict(), cliff4
+        )
+        StabilizerStateTestingTools._verify_individual_bitstrings(
+            self, cliff4.probabilities_dict(), cliff3
+        )
 
         self.assertFalse(cliff1.equiv(cliff3))
         self.assertFalse(cliff2.equiv(cliff4))