qml.measurements.MidMeasureMP¶

class
MidMeasureMP
(wires=None, reset=False, postselect=None, id=None)[source]¶ Bases:
pennylane.measurements.measurements.MeasurementProcess
Midcircuit 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
pennylane.measure()
for detailed documentation. Parameters
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 midcircuit measurement. None by default. If postselection is requested, only the postmeasurement state that is used for postselection will be considered in the remaining circuit.
id (str) – Custom label given to a measurement instance.
Attributes
The data of the measurement.
Whether or not the MeasurementProcess returns a defined decomposition when calling
expand
.Returns an integer hash uniquely representing the measurement process
The name of the measurement.
The Python numeric type of the measurement result.
The wires the measurement process acts on.
Measurement return type.
Whether or not the MeasurementProcess measures in the computational basis.
The wires the measurement process acts on.

data
¶ The data of the measurement. Needed to match the Operator API.

has_decomposition
¶ Whether or not the MeasurementProcess returns a defined decomposition when calling
expand
. Type
Bool

hash
¶ Returns an integer hash uniquely representing the measurement process
 Type
int

name
¶ The name of the measurement. Needed to match the Operator API.

numeric_type
¶ The Python numeric type of the measurement result.
 Returns
The output numeric type;
int
,float
orcomplex
. Return type
type
 Raises
QuantumFunctionError – the return type of the measurement process is unrecognized and cannot deduce the numeric type

raw_wires
¶ The wires the measurement process acts on.
For measurements involving more than one set of wires (such as mutual information), this is a list of the Wires objects. Otherwise, this is the same as
wires()

return_type
¶

samples_computational_basis
¶

wires
¶ The wires the measurement process acts on.
This is the union of all the Wires objects of the measurement.
Methods
Returns the gates that diagonalize the measured wires such that they are in the eigenbasis of the circuit observables.
eigvals
()Eigenvalues associated with the measurement process.
expand
()Expand the measurement of an observable to a unitary rotation and a measurement in the computational basis.
label
([decimals, base_label, cache])How the midcircuit measurement is represented in diagrams and drawings.
map_wires
(wire_map)Returns a copy of the current measurement process with its wires changed according to the given wire map.
queue
([context])Append the measurement process to an annotated queue.
shape
([shots, num_device_wires])Calculate the shape of the result object tensor.
simplify
()Reduce the depth of the observable to the minimum.

diagonalizing_gates
()¶ Returns the gates that diagonalize the measured wires such that they are in the eigenbasis of the circuit observables.
 Returns
the operations that diagonalize the observables
 Return type
List[Operation]

eigvals
()¶ Eigenvalues associated with the measurement process.
If the measurement process has an associated observable, the eigenvalues will correspond to this observable. Otherwise, they will be the eigenvalues provided when the measurement process was instantiated.
Note that the eigenvalues are not guaranteed to be in any particular order.
Example:
>>> m = MeasurementProcess(Expectation, obs=qml.X(1)) >>> m.eigvals() array([1, 1])
 Returns
eigvals representation
 Return type
array

expand
()¶ Expand the measurement of an observable to a unitary rotation and a measurement in the computational basis.
 Returns
a quantum tape containing the operations required to diagonalize the observable
 Return type
Example:
Consider a measurement process consisting of the expectation value of an Hermitian observable:
>>> H = np.array([[1, 2], [2, 4]]) >>> obs = qml.Hermitian(H, wires=['a']) >>> m = MeasurementProcess(Expectation, obs=obs)
Expanding this out:
>>> tape = m.expand()
We can see that the resulting tape has the qubit unitary applied, and a measurement process with no observable, but the eigenvalues specified:
>>> print(tape.operations) [QubitUnitary(array([[0.89442719, 0.4472136 ], [ 0.4472136 , 0.89442719]]), wires=['a'])] >>> print(tape.measurements[0].eigvals()) [0. 5.] >>> print(tape.measurements[0].obs) None

label
(decimals=None, base_label=None, cache=None)[source]¶ How the midcircuit measurement is represented in diagrams and drawings.
 Parameters
decimals=None (Int) – If
None
, no parameters are included. Else, how to round the parameters.base_label=None (Iterable[str]) – overwrite the nonparameter 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
label to use in drawings
 Return type
str

map_wires
(wire_map)¶ Returns a copy of the current measurement process with its wires changed according to the given wire map.
 Parameters
wire_map (dict) – dictionary containing the old wires as keys and the new wires as values
 Returns
new measurement process
 Return type

queue
(context=<class 'pennylane.queuing.QueuingManager'>)¶ Append the measurement process to an annotated queue.

shape
(shots=None, num_device_wires=0)¶ Calculate the shape of the result object tensor.
 Parameters
shots (Optional[int]) – the number of shots used execute the circuit.
None
indicates an analytic simulation. Shot vectors are handled by calling this method multiple times.num_device_wires (int) – The number of wires that will be used if the measurement is broadcasted across all available wires (
len(mp.wires) == 0
). If the device itself doesn’t provide a number of wires, the number of tape wires will be provided here instead:
 Returns
An arbitrary length tuple of ints. May be an empty tuple.
 Return type
tuple[int,..]
>>> qml.probs(wires=(0,1)).shape() (4,) >>> qml.sample(wires=(0,1)).shape(shots=50) (50, 2) >>> qml.state().shape(num_device_wires=4) (16,) >>> qml.expval(qml.Z(0)).shape() ()

simplify
()¶ Reduce the depth of the observable to the minimum.
 Returns
A measurement process with a simplified observable.
 Return type