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TranspileLayout

qiskit.transpiler.TranspileLayout(initial_layout, input_qubit_mapping, final_layout=None, _input_qubit_count=None, _output_qubit_list=None) GitHub(opens in a new tab)

Bases: object(opens in a new tab)

Layout attributes from output circuit from transpiler.

The transpiler in general is unitary-perserving up to permutations caused by setting and applying initial layout during the Layout Stage and SwapGate insertion during the Routing Stage. To provide an interface to reason about these permutations caused by the transpiler. In general the normal interface to access and reason about the layout transformations made by the transpiler is to use the helper methods defined on this class.

For example, looking at the initial layout, the transpiler can potentially remap the order of the qubits in your circuit as it fits the circuit to the target backend. If the input circuit was:

Then during the layout stage the transpiler reorders the qubits to be:

then the output of the initial_virtual_layout() would be equivalent to:

Layout({
    qr[0]: 2,
    qr[1]: 1,
    qr[2]: 0,
})

(it is also this attribute in the QuantumCircuit.draw() and circuit_drawer() which is used to display the mapping of qubits to positions in circuit visualizations post-transpilation)

Building on this above example for final layout, if the transpiler needed to insert swap gates during routing so the output circuit became:

then the output of the routing_permutation() method would be:

[1, 0, 2]

which maps the qubits at each position to their final position after any swap insertions caused by routing.

There are three public attributes associated with the class, however these are mostly provided for backwards compatibility and represent the internal state from the transpiler. They are defined as:

  • initial_layout - This attribute is used to model the permutation caused by the Layout Stage it contains a Layout object that maps the input QuantumCircuits Qubit objects to the position in the output QuantumCircuit.qubits list.
  • input_qubit_mapping - This attribute is used to retain input ordering of the original QuantumCircuit object. It maps the virtual Qubit object from the original circuit (and initial_layout) to its corresponding position in QuantumCircuit.qubits in the original circuit. This is needed when computing the permutation of the Operator of the circuit (and used by Operator.from_circuit()).
  • final_layout - This is a Layout object used to model the output permutation caused ny any SwapGates inserted into the QuantumCircuit during the Routing Stage. It maps the output circuit’s qubits from QuantumCircuit.qubits in the output circuit to the final position after routing. It is not a mapping from the original input circuit’s position to the final position at the end of the transpiled circuit. If you need this you can use the final_index_layout() to generate this. If this is set to None this indicates that routing was not run and it can be considered equivalent to a trivial layout with the qubits from the output circuit’s qubits list.

Attributes

final_layout

Layout | None

= None

initial_layout

Layout

input_qubit_mapping

dict[circuit.Qubit, int]


Methods

final_index_layout

final_index_layout(filter_ancillas=True) GitHub(opens in a new tab)

Generate the final layout as an array of integers

This method will generate an array of final positions for each qubit in the output circuit. For example, if you had an input circuit like:

qc = QuantumCircuit(3)
qc.h(0)
qc.cx(0, 1)
qc.cx(0, 2)

and the output from the transpiler was:

tqc = QuantumCircuit(3)
qc.h(2)
qc.cx(2, 1)
qc.swap(0, 1)
qc.cx(2, 1)

then the return from this function would be a list of:

[2, 0, 1]

because qubit 0 in the original circuit’s final state is on qubit 3 in the output circuit, qubit 1 in the original circuit’s final state is on qubit 0, and qubit 2’s final state is on qubit. The output list length will be as wide as the input circuit’s number of qubits, as the output list from this method is for tracking the permutation of qubits in the original circuit caused by the transpiler.

Parameters

filter_ancillas (bool(opens in a new tab)) – If set to False any ancillas allocated in the output circuit will be included in the layout.

Returns

A list of final positions for each input circuit qubit

Return type

List(opens in a new tab)[int(opens in a new tab)]

final_virtual_layout

final_virtual_layout(filter_ancillas=True) GitHub(opens in a new tab)

Generate the final layout as a Layout object

This method will generate an array of final positions for each qubit in the output circuit. For example, if you had an input circuit like:

qc = QuantumCircuit(3)
qc.h(0)
qc.cx(0, 1)
qc.cx(0, 2)

and the output from the transpiler was:

tqc = QuantumCircuit(3)
qc.h(2)
qc.cx(2, 1)
qc.swap(0, 1)
qc.cx(2, 1)

then the return from this function would be a layout object:

Layout({
    qc.qubits[0]: 2,
    qc.qubits[1]: 0,
    qc.qubits[2]: 1,
})

because qubit 0 in the original circuit’s final state is on qubit 3 in the output circuit, qubit 1 in the original circuit’s final state is on qubit 0, and qubit 2’s final state is on qubit. The output list length will be as wide as the input circuit’s number of qubits, as the output list from this method is for tracking the permutation of qubits in the original circuit caused by the transpiler.

Parameters

filter_ancillas (bool(opens in a new tab)) – If set to False any ancillas allocated in the output circuit will be included in the layout.

Returns

A layout object mapping to the final positions for each qubit

Return type

Layout

initial_index_layout

initial_index_layout(filter_ancillas=False) GitHub(opens in a new tab)

Generate an initial layout as an array of integers

Parameters

filter_ancillas (bool(opens in a new tab)) – If set to True any ancilla qubits added to the transpiler will not be included in the output.

Returns

A layout array that maps a position in the array to its new position in the output circuit.

Return type

List(opens in a new tab)[int(opens in a new tab)]

initial_virtual_layout

initial_virtual_layout(filter_ancillas=False) GitHub(opens in a new tab)

Return a Layout object for the initial layout.

This returns a mapping of virtual Qubit objects in the input circuit to the physical qubit selected during layout. This is analogous to the initial_layout attribute.

Parameters

filter_ancillas (bool(opens in a new tab)) – If set to True only qubits in the input circuit will be in the returned layout. Any ancilla qubits added to the output circuit will be filtered from the returned object.

Returns

A layout object mapping the input circuit’s Qubit objects to the selected physical qubits.

Return type

Layout

routing_permutation

routing_permutation() GitHub(opens in a new tab)

Generate a final layout as an array of integers

If there is no final_layout attribute present then that indicates there was no output permutation caused by routing or other transpiler transforms. In this case the function will return a list of [0, 1, 2, .., n] to indicate this

Returns

A layout array that maps a position in the array to its new position in the output circuit

Return type

List(opens in a new tab)[int(opens in a new tab)]

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