qml.measurements.ClassicalShadowMP¶

class ClassicalShadowMP(wires=None, seed=None, id=None)[source]¶

Bases: pennylane.measurements.measurements.MeasurementTransform

Represents a classical shadow measurement process occurring at the end of a quantum variational circuit.

Please refer to classical_shadow() for detailed documentation.

Parameters

wires (Wires) – The wires the measurement process applies to.
seed (Union[int, None]) – The seed used to generate the random measurements
id (str) – custom label given to a measurement instance, can be useful for some applications where the instance has to be identified

Attributes

`has_decomposition`	Whether or not the MeasurementProcess returns a defined decomposition when calling `expand`.
`hash`	returns an integer hash uniquely representing the measurement process
`numeric_type`	The Python numeric type of the measurement result.
`raw_wires`	The wires the measurement process acts on.
`return_type`	Measurement return type.
`samples_computational_basis`	Whether or not the MeasurementProcess measures in the computational basis.
`wires`	The wires the measurement process acts on.

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

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

`diagonalizing_gates`()	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.
`map_wires`(wire_map)	Returns a copy of the current measurement process with its wires changed according to the given wire map.
`process`(tape, device)	Returns the measured bits and recipes in the classical shadow protocol.
`process_state_with_shots`(state, wire_order, …)	Process the given quantum state with the given number of shots
`queue`([context])	Append the measurement process to an annotated queue.
`shape`(device, shots)	The expected output shape of the MeasurementProcess.
`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.PauliX(wires=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: QuantumTape

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

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: MeasurementProcess

process(tape, device)[source]¶

Returns the measured bits and recipes in the classical shadow protocol.

The protocol is described in detail in the classical shadows paper. This measurement process returns the randomized Pauli measurements (the recipes) that are performed for each qubit and snapshot as an integer:

0 for Pauli X,
1 for Pauli Y, and
2 for Pauli Z.

It also returns the measurement results (the bits); 0 if the 1 eigenvalue is sampled, and 1 if the -1 eigenvalue is sampled.

The device shots are used to specify the number of snapshots. If T is the number of shots and n is the number of qubits, then both the measured bits and the Pauli measurements have shape (T, n).

This implementation is device-agnostic and works by executing single-shot quantum tapes containing randomized Pauli observables. Devices should override this if they can offer cleaner or faster implementations.

qml.measurements.ClassicalShadowMP¶

Attributes

Methods

Contents

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qml.measurements.ClassicalShadowMP¶

Attributes

Methods

Contents

Downloads

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