Merge branch 'master' into prob-interface-in-probs-process-density-ma…

…trix

doc/releases/changelog-dev.md

@@ -341,6 +341,9 @@ such as `shots`, `rng` and `prng_key`.
 
 <h4>Other Improvements</h4>
 
+* `Wires` object usage across Pennylane source code has been tidied up.
+  [(#6689)](https://github.com/PennyLaneAI/pennylane/pull/6689)
+
 * `qml.equal` now supports `PauliWord` and `PauliSentence` instances.
   [(#6703)](https://github.com/PennyLaneAI/pennylane/pull/6703)
 
@@ -375,6 +378,7 @@ such as `shots`, `rng` and `prng_key`.
 
 * PennyLane is compatible with `quimb 1.10.0`.
   [(#6630)](https://github.com/PennyLaneAI/pennylane/pull/6630)
+  [(#6736)](https://github.com/PennyLaneAI/pennylane/pull/6736)
 
 * Add developer focused `run` function to `qml.workflow` module.
   [(#6657)](https://github.com/PennyLaneAI/pennylane/pull/6657)

pennylane/devices/default_tensor.py

@@ -226,8 +226,8 @@ class DefaultTensor(Device):
             `quimb's tensor_contract documentation <https://quimb.readthedocs.io/en/latest/autoapi/quimb/tensor/tensor_core/index.html#quimb.tensor.tensor_core.tensor_contract>`_.
             Default is ``"auto-hq"``.
         local_simplify (str): The simplification sequence to apply to the tensor network for computing local expectation values.
-            For a complete list of available simplification options, see the
-            `quimb's full_simplify documentation <https://quimb.readthedocs.io/en/latest/autoapi/quimb/tensor/tensor_core/index.html#quimb.tensor.tensor_core.TensorNetwork.full_simplify>`_.
+            At present, this argument can only be provided when the TN method is used. For a complete list of available simplification options,
+            see the `quimb's full_simplify documentation <https://quimb.readthedocs.io/en/latest/autoapi/quimb/tensor/tensor_core/index.html#quimb.tensor.tensor_core.TensorNetwork.full_simplify>`_.
             Default is ``"ADCRS"``.
 
 
@@ -400,8 +400,10 @@ def __init__(
         self._max_bond_dim = kwargs.get("max_bond_dim", None)
         self._cutoff = kwargs.get("cutoff", None)
 
-        # options both for MPS and TN
+        # options for TN
         self._local_simplify = kwargs.get("local_simplify", "ADCRS")
+
+        # options both for MPS and TN
         self._contraction_optimizer = kwargs.get("contraction_optimizer", "auto-hq")
         self._contract = None
 
@@ -810,14 +812,22 @@ def _local_expectation(self, matrix, wires) -> float:
         # after the execution, we could avoid copying the circuit.
         qc = self._quimb_circuit.copy()
 
-        exp_val = qc.local_expectation(
-            matrix,
-            wires,
-            dtype=self._c_dtype.__name__,
-            optimize=self._contraction_optimizer,
-            simplify_sequence=self._local_simplify,
-            simplify_atol=0.0,
-        )
+        if self.method == "mps":
+            exp_val = qc.local_expectation(
+                matrix,
+                wires,
+                dtype=self._c_dtype.__name__,
+                optimize=self._contraction_optimizer,
+            )
+        else:
+            exp_val = qc.local_expectation(
+                matrix,
+                wires,
+                dtype=self._c_dtype.__name__,
+                optimize=self._contraction_optimizer,
+                simplify_sequence=self._local_simplify,
+                simplify_atol=0.0,
+            )
 
         return float(np.real(exp_val))
 

pennylane/measurements/classical_shadow.py

@@ -23,7 +23,7 @@
 
 import pennylane as qml
 from pennylane.operation import Operator
-from pennylane.wires import Wires
+from pennylane.wires import Wires, WiresLike
 
 from .measurements import MeasurementShapeError, MeasurementTransform, Shadow, ShadowExpval
 
@@ -89,7 +89,7 @@ def circuit(x, obs):
     return ShadowExpvalMP(H=H, seed=seed, k=k)
 
 
-def classical_shadow(wires, seed=None):
+def classical_shadow(wires: WiresLike, seed=None):
     """
     The classical shadow measurement protocol.
 
@@ -227,7 +227,10 @@ class ClassicalShadowMP(MeasurementTransform):
     """
 
     def __init__(
-        self, wires: Optional[Wires] = None, seed: Optional[int] = None, id: Optional[str] = None
+        self,
+        wires: Optional[WiresLike] = None,
+        seed: Optional[int] = None,
+        id: Optional[str] = None,
     ):
         self.seed = seed
         super().__init__(wires=wires, id=id)

pennylane/ops/channel.py

@@ -20,6 +20,7 @@
 
 from pennylane import math as np
 from pennylane.operation import AnyWires, Channel
+from pennylane.wires import Wires, WiresLike
 
 
 class AmplitudeDamping(Channel):
@@ -58,7 +59,8 @@ class AmplitudeDamping(Channel):
     num_wires = 1
     grad_method = "F"
 
-    def __init__(self, gamma, wires, id=None):
+    def __init__(self, gamma, wires: WiresLike, id=None):
+        wires = Wires(wires)
         super().__init__(gamma, wires=wires, id=id)
 
     @staticmethod
@@ -563,7 +565,8 @@ class PauliError(Channel):
     num_params = 2
     """int: Number of trainable parameters that the operator depends on."""
 
-    def __init__(self, operators, p, wires=None, id=None):
+    def __init__(self, operators, p, wires: WiresLike, id=None):
+        wires = Wires(wires)
         super().__init__(operators, p, wires=wires, id=id)
 
         # check if the specified operators are legal
@@ -713,7 +716,8 @@ class QubitChannel(Channel):
     num_wires = AnyWires
     grad_method = None
 
-    def __init__(self, K_list, wires=None, id=None):
+    def __init__(self, K_list, wires: WiresLike, id=None):
+        wires = Wires(wires)
         super().__init__(*K_list, wires=wires, id=id)
 
         # check all Kraus matrices are square matrices
@@ -744,7 +748,8 @@ def _flatten(self):
 
     # pylint: disable=arguments-differ, unused-argument
     @classmethod
-    def _primitive_bind_call(cls, K_list, wires=None, id=None):
+    def _primitive_bind_call(cls, K_list, wires: WiresLike, id=None):
+        wires = Wires(wires)
         return super()._primitive_bind_call(*K_list, wires=wires)
 
     @staticmethod

pennylane/ops/identity.py

@@ -27,6 +27,7 @@
     Operation,
     SparseMatrixUndefinedError,
 )
+from pennylane.wires import WiresLike
 
 
 class Identity(CVObservable, Operation):
@@ -61,15 +62,16 @@ class Identity(CVObservable, Operation):
     ev_order = 1
 
     @classmethod
-    def _primitive_bind_call(cls, wires=None, **kwargs):  # pylint: disable=arguments-differ
-        wires = [] if wires is None else wires
+    def _primitive_bind_call(
+        cls, wires: WiresLike = (), **kwargs
+    ):  # pylint: disable=arguments-differ
         return super()._primitive_bind_call(wires=wires, **kwargs)
 
     def _flatten(self):
         return tuple(), (self.wires, tuple())
 
-    def __init__(self, wires=None, id=None):
-        super().__init__(wires=[] if wires is None else wires, id=id)
+    def __init__(self, wires: WiresLike = (), id=None):
+        super().__init__(wires=wires, id=id)
         self._hyperparameters = {"n_wires": len(self.wires)}
         self._pauli_rep = qml.pauli.PauliSentence({qml.pauli.PauliWord({}): 1.0})
 
@@ -308,12 +310,13 @@ def circuit():
     grad_method = None
 
     @classmethod
-    def _primitive_bind_call(cls, phi, wires=None, **kwargs):  # pylint: disable=arguments-differ
-        wires = [] if wires is None else wires
+    def _primitive_bind_call(
+        cls, phi, wires: WiresLike = (), **kwargs
+    ):  # pylint: disable=arguments-differ
         return super()._primitive_bind_call(phi, wires=wires, **kwargs)
 
-    def __init__(self, phi, wires=None, id=None):
-        super().__init__(phi, wires=[] if wires is None else wires, id=id)
+    def __init__(self, phi, wires: WiresLike = (), id=None):
+        super().__init__(phi, wires=wires, id=id)
 
     @staticmethod
     def compute_eigvals(phi, n_wires=1):  # pylint: disable=arguments-differ
@@ -412,7 +415,9 @@ def compute_diagonalizing_gates(
         return []
 
     @staticmethod
-    def compute_decomposition(phi, wires=None):  # pylint:disable=arguments-differ,unused-argument
+    def compute_decomposition(
+        phi, wires: WiresLike = ()
+    ):  # pylint:disable=arguments-differ,unused-argument
         r"""Representation of the operator as a product of other operators (static method).
 
         .. note::

pennylane/ops/meta.py

@@ -23,7 +23,7 @@
 
 import pennylane as qml
 from pennylane.operation import AnyWires, Operation
-from pennylane.wires import Wires  # pylint: disable=unused-import
+from pennylane.wires import Wires, WiresLike
 
 
 class Barrier(Operation):
@@ -46,7 +46,8 @@ class Barrier(Operation):
     num_wires = AnyWires
     par_domain = None
 
-    def __init__(self, wires=Wires([]), only_visual=False, id=None):
+    def __init__(self, wires: WiresLike = (), only_visual=False, id=None):
+        wires = Wires(wires)
         self.only_visual = only_visual
         self.hyperparameters["only_visual"] = only_visual
         super().__init__(wires=wires, id=id)
@@ -119,16 +120,12 @@ class WireCut(Operation):
     num_wires = AnyWires
     grad_method = None
 
-    def __init__(self, *params, wires=None, id=None):
-        if wires == []:
-            raise ValueError(
-                f"{self.__class__.__name__}: wrong number of wires. "
-                f"At least one wire has to be given."
-            )
-        super().__init__(*params, wires=wires, id=id)
+    def __init__(self, wires: WiresLike = (), id=None):
+        wires = Wires(wires)
+        super().__init__(wires=wires, id=id)
 
     @staticmethod
-    def compute_decomposition(wires):  # pylint: disable=unused-argument
+    def compute_decomposition(wires: WiresLike):  # pylint: disable=unused-argument
         r"""Representation of the operator as a product of other operators (static method).
 
         Since this operator is a placeholder inside a circuit, it decomposes into an empty list.

pennylane/ops/op_math/controlled.py

@@ -31,7 +31,7 @@
 from pennylane.capture.capture_diff import create_non_interpreted_prim
 from pennylane.compiler import compiler
 from pennylane.operation import Operator
-from pennylane.wires import Wires
+from pennylane.wires import Wires, WiresLike
 
 from .controlled_decompositions import ctrl_decomp_bisect, ctrl_decomp_zyz
 from .symbolicop import SymbolicOp
@@ -175,7 +175,7 @@ def create_controlled_op(op, control, control_values=None, work_wires=None):
     # Flatten nested controlled operations to a multi-controlled operation for better
     # decomposition algorithms. This includes special cases like CRX, CRot, etc.
     if isinstance(op, Controlled):
-        work_wires = work_wires or []
+        work_wires = () if work_wires is None else work_wires
         return ctrl(
             op.base,
             control=control + op.control_wires,
@@ -489,9 +489,16 @@ def _primitive_bind_call(
         )
 
     # pylint: disable=too-many-function-args
-    def __init__(self, base, control_wires, control_values=None, work_wires=None, id=None):
+    def __init__(
+        self,
+        base,
+        control_wires: WiresLike,
+        control_values=None,
+        work_wires: WiresLike = None,
+        id=None,
+    ):
         control_wires = Wires(control_wires)
-        work_wires = Wires([]) if work_wires is None else Wires(work_wires)
+        work_wires = Wires(() if work_wires is None else work_wires)
 
         if control_values is None:
             control_values = [True] * len(control_wires)

pennylane/ops/op_math/controlled_ops.py

@@ -1155,7 +1155,16 @@ def _primitive_bind_call(cls, wires, control_values=None, work_wires=None, id=No
         )
 
     # pylint: disable=too-many-arguments
-    def __init__(self, control_wires=None, wires=None, control_values=None, work_wires=None):
+    def __init__(
+        self,
+        control_wires: WiresLike = (),
+        wires: WiresLike = (),
+        control_values=None,
+        work_wires: WiresLike = (),
+    ):
+        control_wires = Wires(() if control_wires is None else control_wires)
+        wires = Wires(() if wires is None else wires)
+        work_wires = Wires(() if work_wires is None else work_wires)
 
         # First raise deprecation warnings regardless of the validity of other arguments
         if isinstance(control_values, str):
@@ -1164,22 +1173,19 @@ def __init__(self, control_wires=None, wires=None, control_values=None, work_wir
                 "supported in future releases, Use a list of booleans or integers instead.",
                 qml.PennyLaneDeprecationWarning,
             )
-        if control_wires is not None:
+        if len(control_wires) > 0:
             warnings.warn(
                 "The control_wires keyword for MultiControlledX is deprecated, and will "
                 "be removed soon. Use wires = (*control_wires, target_wire) instead.",
                 UserWarning,
             )
 
-        if wires is None:
+        if len(wires) == 0:
             raise ValueError("Must specify the wires where the operation acts on")
 
-        wires = wires if isinstance(wires, Wires) else Wires(wires)
-
-        if control_wires is not None:
+        if len(control_wires) > 0:
             if len(wires) != 1:
                 raise ValueError("MultiControlledX accepts a single target wire.")
-            control_wires = Wires(control_wires)
         else:
             if len(wires) < 2:
                 raise ValueError(
@@ -1212,7 +1218,7 @@ def wires(self):
 
     # pylint: disable=unused-argument, arguments-differ
     @staticmethod
-    def compute_matrix(control_wires, control_values=None, **kwargs):
+    def compute_matrix(control_wires: WiresLike, control_values=None, **kwargs):
         r"""Representation of the operator as a canonical matrix in the computational basis (static method).
 
         The canonical matrix is the textbook matrix representation that does not consider wires.
@@ -1255,7 +1261,9 @@ def matrix(self, wire_order=None):
 
     # pylint: disable=unused-argument, arguments-differ
     @staticmethod
-    def compute_decomposition(wires=None, work_wires=None, control_values=None, **kwargs):
+    def compute_decomposition(
+        wires: WiresLike = None, work_wires: WiresLike = None, control_values=None, **kwargs
+    ):
         r"""Representation of the operator as a product of other operators (static method).
 
         .. math:: O = O_1 O_2 \dots O_n.
@@ -1282,6 +1290,7 @@ def compute_decomposition(wires=None, work_wires=None, control_values=None, **kw
         Toffoli(wires=[0, 1, 'aux'])]
 
         """
+        wires = Wires(() if wires is None else wires)
 
         if len(wires) < 2:
             raise ValueError(f"Wrong number of wires. {len(wires)} given. Need at least 2.")
@@ -1357,7 +1366,7 @@ class CRX(ControlledOp):
     name = "CRX"
     parameter_frequencies = [(0.5, 1.0)]
 
-    def __init__(self, phi, wires, id=None):
+    def __init__(self, phi, wires: WiresLike, id=None):
         # We use type.__call__ instead of calling the class directly so that we don't bind the
         # operator primitive when new program capture is enabled
         base = type.__call__(qml.RX, phi, wires=wires[1:])
@@ -1374,7 +1383,7 @@ def _unflatten(cls, data, metadata):
         return cls(*data, wires=metadata[0])
 
     @classmethod
-    def _primitive_bind_call(cls, phi, wires, id=None):
+    def _primitive_bind_call(cls, phi, wires: WiresLike, id=None):
         return cls._primitive.bind(phi, *wires, n_wires=len(wires))
 
     @staticmethod
@@ -1425,7 +1434,7 @@ def compute_matrix(theta):  # pylint: disable=arguments-differ
         return qml.math.stack([stack_last(row) for row in matrix], axis=-2)
 
     @staticmethod
-    def compute_decomposition(phi, wires):  # pylint: disable=arguments-differ
+    def compute_decomposition(phi, wires: WiresLike):  # pylint: disable=arguments-differ
         r"""Representation of the operator as a product of other operators (static method). :
 
         .. math:: O = O_1 O_2 \dots O_n.

pennylane/ops/qubit/non_parametric_ops.py

@@ -252,7 +252,7 @@ def pauli_rep(self):
             )
         return self._pauli_rep
 
-    def __init__(self, wires: Optional[WiresLike] = None, id: Optional[str] = None):
+    def __init__(self, wires: WiresLike, id: Optional[str] = None):
         super().__init__(wires=wires, id=id)
 
     def label(