Source code for pennylane.ops.mid_measure.mid_measure
# Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This module contains the qml.measure measurement.
"""
import uuid
from collections.abc import Hashable
from functools import lru_cache
from pennylane.capture import enabled as capture_enabled
from pennylane.compiler import compiler
from pennylane.exceptions import QuantumFunctionError
from pennylane.operation import Operator
from pennylane.wires import Wires
from .measurement_value import MeasurementValue
def _measure_impl(wires: Hashable | Wires, reset: bool = False, postselect: int | None = None):
"""Concrete implementation of qml.measure"""
wires = Wires(wires)
if len(wires) > 1:
raise QuantumFunctionError(
"Only a single qubit can be measured in the middle of the circuit"
)
# Create a UUID and a map between MP and MV to support serialization
measurement_id = str(uuid.uuid4())
mp = MidMeasure(wires=wires, reset=reset, postselect=postselect, id=measurement_id)
return MeasurementValue([mp])
@lru_cache
def _create_mid_measure_primitive():
"""Create a primitive corresponding to an mid-circuit measurement type.
Called when using :func:`~pennylane.measure`.
Returns:
jax.extend.core.Primitive: A new jax primitive corresponding to a mid-circuit
measurement.
"""
# pylint: disable=import-outside-toplevel
import jax
from pennylane.capture.custom_primitives import QmlPrimitive
mid_measure_p = QmlPrimitive("measure")
@mid_measure_p.def_impl
def _impl(wires, reset=False, postselect=None):
return _measure_impl(wires, reset=reset, postselect=postselect)
@mid_measure_p.def_abstract_eval
def _abstract_eval(*_, **__):
dtype = jax.numpy.int64 if jax.config.jax_enable_x64 else jax.numpy.int32
return jax.core.ShapedArray((), dtype)
return mid_measure_p
def get_mcm_predicates(conditions: tuple[MeasurementValue]) -> list[MeasurementValue]:
r"""Function to make mid-circuit measurement predicates mutually exclusive.
The ``conditions`` are predicates to the ``if`` and ``elif`` branches of ``qml.cond``.
This function updates all the ``MeasurementValue``\ s in ``conditions`` such that
reconciling the correct branch is never ambiguous.
Args:
conditions (Sequence[MeasurementValue]): Sequence containing predicates for ``if``
and all ``elif`` branches of a function decorated with :func:`~pennylane.cond`.
Returns:
Sequence[MeasurementValue]: Updated sequence of mutually exclusive predicates.
"""
new_conds = [conditions[0]]
false_cond = ~conditions[0]
for c in conditions[1:]:
new_conds.append(false_cond & c)
false_cond = false_cond & ~c
new_conds.append(false_cond)
return new_conds
class MidMeasure(Operator):
"""Mid-circuit measurement.
This class additionally stores information about unknown measurement outcomes in the qubit model.
Measurements on a single qubit in the computational basis are assumed.
Please refer to :func:`pennylane.measure` for detailed documentation.
Args:
wires (.Wires): The wires the measurement process applies to.
This can only be specified if an observable was not provided.
reset (bool): Whether to reset the wire after measurement.
postselect (Optional[int]): Which basis state to postselect after a mid-circuit
measurement. None by default. If postselection is requested, only the post-measurement
state that is used for postselection will be considered in the remaining circuit.
id (str): Custom label given to a measurement instance.
"""
def __repr__(self):
return f"MidMeasure(wires={list(self.wires)}, postselect={self.postselect}, reset={self.reset})"
num_wires = 1
num_params = 0
batch_size = None
resource_keys = set()
def __init__(
self,
wires: Wires | None = None,
reset: bool = False,
postselect: int | None = None,
id: str | None = None,
):
super().__init__(wires=Wires(wires), id=id)
self._hyperparameters = {"reset": reset, "postselect": postselect, "id": id}
self._name = "MidMeasureMP"
@property
def reset(self) -> bool:
"""Whether to reset the wire into the zero state after the measurement."""
return self.hyperparameters["reset"]
@property
def postselect(self) -> int | None:
"""Which basis state to postselect after a mid-circuit measurement."""
return self.hyperparameters["postselect"]
@classmethod
def _primitive_bind_call(cls, *args, **kwargs):
return type.__call__(cls, *args, **kwargs)
@staticmethod
def compute_diagonalizing_gates(*params, wires, **hyperparams) -> list[Operator]:
return []
def label(self, decimals=None, base_label=None, cache=None):
r"""How the mid-circuit measurement is represented in diagrams and drawings.
Args:
decimals=None (Int): If ``None``, no parameters are included. Else,
how to round the parameters.
base_label=None (Iterable[str]): overwrite the non-parameter component of the label.
Must be same length as ``obs`` attribute.
cache=None (dict): dictionary that carries information between label calls
in the same drawing
Returns:
str: label to use in drawings
"""
_label = "┤↗"
if self.postselect is not None:
_label += "₁" if self.postselect == 1 else "₀"
_label += "├" if not self.reset else "│ │0⟩"
return _label
@property
def resource_params(self) -> dict:
return {}
@property
def hash(self):
"""int: Returns an integer hash uniquely representing the measurement process"""
return hash((self.__class__.__name__, tuple(self.wires.tolist()), self.id))
[docs]
def measure(
wires: Hashable | Wires, reset: bool = False, postselect: int | None = None
) -> MeasurementValue:
r"""Perform a mid-circuit measurement in the computational basis on the
supplied qubit.
Args:
wires (Wires): The wire to measure.
reset (bool): Whether to reset the wire to the :math:`|0 \rangle`
state after measurement.
postselect (Optional[int]): Which basis state to postselect after a mid-circuit
measurement. None by default. If postselection is requested, only the post-measurement
state that is used for postselection will be considered in the remaining circuit.
Returns:
MeasurementValue: A reference to the future result of the mid circuit measurement
Raises:
QuantumFunctionError: if multiple wires were specified
Computational basis measurements are performed using the 0, 1 convention
rather than the ±1 convention.
Measurement outcomes can be used to conditionally apply operations, and measurement
statistics can be gathered and returned by a quantum function.
If a device doesn't support mid-circuit measurements natively, then the
QNode will apply the :func:`defer_measurements` transform.
**Example:**
.. code-block:: python
dev = qml.device("default.qubit", wires=3)
@qml.qnode(dev)
def func(x, y):
qml.RY(x, wires=0)
qml.CNOT(wires=[0, 1])
m_0 = qml.measure(1)
qml.cond(m_0, qml.RY)(y, wires=0)
return qml.probs(wires=[0])
Executing this QNode:
>>> pars = np.array([0.643, 0.246])
>>> func(*pars)
array([0.901..., 0.0983...])
Wires can be reused after measurement. Moreover, measured wires can be reset
to the :math:`|0 \rangle` state by setting ``reset=True``.
.. code-block:: python
dev = qml.device("default.qubit", wires=3)
@qml.qnode(dev)
def func():
qml.X(1)
m_0 = qml.measure(1, reset=True)
return qml.probs(wires=[1])
Executing this QNode:
>>> func()
array([1., 0.])
Mid-circuit measurements can be manipulated using the following arithmetic operators:
``+``, ``-``, ``*``, ``/``, ``~`` (not), ``&`` (and), ``|`` (or), ``==``, ``<=``,
``>=``, ``<``, ``>`` with other mid-circuit measurements or scalars.
.. Note ::
Python ``not``, ``and``, ``or``, do not work since these do not have dunder methods.
Instead use ``~``, ``&``, ``|``.
Mid-circuit measurement results can be processed with the usual measurement functions such as
:func:`~.expval`. For QNodes with finite shots, :func:`~.sample` applied to a mid-circuit measurement
result will return a binary sequence of samples.
See :ref:`here <mid_circuit_measurements_statistics>` for more details.
.. Note ::
Computational basis measurements are performed using the 0, 1 convention rather than the ±1 convention.
So, for example, ``expval(qml.measure(0))`` and ``expval(qml.Z(0))`` will give different answers.
.. code-block:: python
dev = qml.device("default.qubit", seed=1234)
@qml.qnode(dev)
def circuit(x, y):
qml.RX(x, wires=0)
qml.RY(y, wires=1)
m0 = qml.measure(1)
return (
qml.sample(m0), qml.expval(m0), qml.var(m0), qml.probs(op=m0), qml.counts(op=m0),
)
>>> qml.set_shots(circuit, shots=1000)(1.0, 2.0)
(array([0, 1, 0, ... 1, 0, 1]), np.float64(0.713), np.float64(0.2046...), array([0.287, 0.713]), {0.0: np.int64(287), 1.0: np.int64(713)})
.. details::
:title: Postselection
Postselection discards outcomes that do not meet the criteria provided by the ``postselect``
argument. For example, specifying ``postselect=1`` on wire 0 would be equivalent to projecting
the state vector onto the :math:`|1\rangle` state on wire 0:
.. code-block:: python
dev = qml.device("default.qubit", seed=1234)
@qml.qnode(dev)
def func(x):
qml.RX(x, wires=0)
m0 = qml.measure(0, postselect=1)
qml.cond(m0, qml.X)(wires=1)
return qml.sample(wires=1)
By postselecting on ``1``, we only consider the ``1`` measurement outcome on wire 0. So, the probability of
measuring ``1`` on wire 1 after postselection should also be 1. Executing this QNode with 10 shots:
>>> qml.set_shots(func, 10)(np.pi / 2)
array([[1],
[1],
[1],
[1],
[1],
[1]])
Note that less than 10 samples are returned. This is because samples that do not meet the postselection criteria are
thrown away.
If postselection is requested on a state with zero probability of being measured, the result may contain ``NaN``
or ``Inf`` values:
.. code-block:: python
dev = qml.device("default.qubit")
@qml.qnode(dev)
def func(x):
qml.RX(x, wires=0)
m0 = qml.measure(0, postselect=1)
qml.cond(m0, qml.X)(wires=1)
return qml.probs(wires=1)
>>> func(0.0)
array([nan, nan])
In the case of ``qml.sample`` and `mcm_method="deferred"`, an empty array will be returned:
.. code-block:: python
dev = qml.device("default.qubit")
@qml.qnode(dev, mcm_method="deferred")
def func(x):
qml.RX(x, wires=0)
m0 = qml.measure(0, postselect=1)
qml.cond(m0, qml.X)(wires=1)
return qml.sample(wires=[0, 1])
>>> qml.set_shots(func, shots=[10, 10])(0.0)
(array([], shape=(0, 2), dtype=int64), array([], shape=(0, 2), dtype=int64))
.. note::
Currently, postselection support is only available on ``default.qubit``. Using postselection
on other devices will raise an error.
.. warning::
All measurements are supported when using postselection. However, postselection on a zero probability
state can cause some measurements to break:
* With finite shots, one must be careful when measuring ``qml.probs`` or ``qml.counts``, as these
measurements will raise errors if there are no valid samples after postselection. This will occur
with postselection states that have zero or close to zero probability.
* With analytic execution, ``qml.mutual_info`` will raise errors when using any interfaces except
``jax``, and ``qml.vn_entropy`` will raise an error with the ``tensorflow`` interface when the
postselection state has zero probability.
* When using JIT, ``QNode``'s may have unexpected behaviour when postselection on a zero
probability state is performed. Due to floating point precision, the zero probability may not be
detected, thus letting execution continue as normal without ``NaN`` or ``Inf`` values or empty
samples, leading to unexpected or incorrect results.
"""
if capture_enabled():
primitive = _create_mid_measure_primitive()
return primitive.bind(wires, reset=reset, postselect=postselect)
if active_jit := compiler.active_compiler():
available_eps = compiler.AvailableCompilers.names_entrypoints
ops_loader = available_eps[active_jit]["ops"].load()
return ops_loader.measure(wires, reset=reset, postselect=postselect)
return _measure_impl(wires, reset=reset, postselect=postselect)
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