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class qiskit.circuit.library.ExcitationPreserving(num_qubits=None, mode='iswap', entanglement='full', reps=3, skip_unentangled_qubits=False, skip_final_rotation_layer=False, parameter_prefix='θ', insert_barriers=False, initial_state=None, name='ExcitationPreserving', flatten=None)

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Bases: TwoLocal

The heuristic excitation-preserving wave function ansatz.

The ExcitationPreserving circuit preserves the ratio of 00|00\rangle, 01+10|01\rangle + |10\rangle and 11|11\rangle states. To this end, this circuit uses two-qubit interactions of the form

(10000cos(θ/2)isin(θ/2)00isin(θ/2)cos(θ/2)0000eiϕ)\providecommand{\rotationangle}{\theta/2} \begin{pmatrix} 1 & 0 & 0 & 0 \\ 0 & \cos\left(\rotationangle\right) & -i\sin\left(\rotationangle\right) & 0 \\ 0 & -i\sin\left(\rotationangle\right) & \cos\left(\rotationangle\right) & 0 \\ 0 & 0 & 0 & e^{-i\phi} \end{pmatrix}

for the mode 'fsim' or with eiϕ=1e^{-i\phi} = 1 for the mode 'iswap'.

Note that other wave functions, such as UCC-ansatzes, are also excitation preserving. However these can become complex quickly, while this heuristically motivated circuit follows a simpler pattern.

This trial wave function consists of layers of ZZ rotations with 2-qubit entanglements. The entangling is creating using XX+YYXX+YY rotations and optionally a controlled-phase gate for the mode 'fsim'.

See RealAmplitudes for more detail on the possible arguments and options such as skipping unentanglement qubits, which apply here too.

The rotations of the ExcitationPreserving ansatz can be written as


>>> ansatz = ExcitationPreserving(3, reps=1, insert_barriers=True, entanglement='linear')
>>> print(ansatz)  # show the circuit
     ┌──────────┐ ░ ┌────────────┐┌────────────┐                             ░ ┌──────────┐
q_0:RZ(θ[0]) ├─░─┤0           ├┤0           ├─────────────────────────────░─┤ RZ(θ[5])
     ├──────────┤ ░ │  RXX(θ[3]) ││  RYY(θ[3]) │┌────────────┐┌────────────┐ ░ ├──────────┤
q_1:RZ(θ[1]) ├─░─┤1           ├┤1           ├┤0           ├┤0           ├─░─┤ RZ(θ[6])
     ├──────────┤ ░ └────────────┘└────────────┘│  RXX(θ[4]) ││  RYY(θ[4]) │ ░ ├──────────┤
q_2:RZ(θ[2]) ├─░─────────────────────────────┤1           ├┤1           ├─░─┤ RZ(θ[7])
     └──────────┘ ░                             └────────────┘└────────────┘ ░ └──────────┘
>>> ansatz = ExcitationPreserving(2, reps=1)
>>> qc = QuantumCircuit(2)  # create a circuit and append the RY variational form
>>> qc.cry(0.2, 0, 1)  # do some previous operation
>>> qc.compose(ansatz, inplace=True)  # add the swaprz
>>> qc.draw()
q_0: ─────■─────┤ RZ(θ[0]) ├┤0           ├┤0           ├┤ RZ(θ[3])
     ┌────┴────┐├──────────┤│  RXX(θ[2]) ││  RYY(θ[2]) │├──────────┤
q_1:RY(0.2) ├┤ RZ(θ[1]) ├┤1           ├┤1           ├┤ RZ(θ[4])
>>> ansatz = ExcitationPreserving(3, reps=1, mode='fsim', entanglement=[[0,2]],
... insert_barriers=True)
>>> print(ansatz)
     ┌──────────┐ ░ ┌────────────┐┌────────────┐        ░ ┌──────────┐
q_0:RZ(θ[0]) ├─░─┤0           ├┤0           ├─■──────░─┤ RZ(θ[5])
     ├──────────┤ ░ │            ││            │ │      ░ ├──────────┤
q_1:RZ(θ[1]) ├─░─┤  RXX(θ[3]) ├┤  RYY(θ[3]) ├─┼──────░─┤ RZ(θ[6])
     ├──────────┤ ░ │            ││            │ │θ[4]  ░ ├──────────┤
q_2:RZ(θ[2]) ├─░─┤1           ├┤1           ├─■──────░─┤ RZ(θ[7])
     └──────────┘ ░ └────────────┘└────────────┘        ░ └──────────┘


  • num_qubits (int(opens in a new tab) | None) – The number of qubits of the ExcitationPreserving circuit.
  • mode (str(opens in a new tab)) – Choose the entangler mode, can be ‘iswap’ or ‘fsim’.
  • reps (int(opens in a new tab)) – Specifies how often the structure of a rotation layer followed by an entanglement layer is repeated.
  • entanglement (str(opens in a new tab) |list(opens in a new tab)[list(opens in a new tab)[int(opens in a new tab)]] | Callable[[int(opens in a new tab)], list(opens in a new tab)[int(opens in a new tab)]]) – Specifies the entanglement structure. Can be a string (‘full’, ‘linear’ or ‘sca’), a list of integer-pairs specifying the indices of qubits entangled with one another, or a callable returning such a list provided with the index of the entanglement layer. See the Examples section of TwoLocal for more detail.
  • initial_state (QuantumCircuit | None) – A QuantumCircuit object to prepend to the circuit.
  • skip_unentangled_qubits (bool(opens in a new tab)) – If True, the single qubit gates are only applied to qubits that are entangled with another qubit. If False, the single qubit gates are applied to each qubit in the Ansatz. Defaults to False.
  • skip_final_rotation_layer (bool(opens in a new tab)) – If True, a rotation layer is added at the end of the ansatz. If False, no rotation layer is added. Defaults to True.
  • parameter_prefix (str(opens in a new tab)) – The parameterized gates require a parameter to be defined, for which we use ParameterVector.
  • insert_barriers (bool(opens in a new tab)) – If True, barriers are inserted in between each layer. If False, no barriers are inserted.
  • flatten (bool(opens in a new tab) | None) – Set this to True to output a flat circuit instead of nesting it inside multiple layers of gate objects. By default currently the contents of the output circuit will be wrapped in nested objects for cleaner visualization. However, if you’re using this circuit for anything besides visualization its strongly recommended to set this flag to True to avoid a large performance overhead for parameter binding.


ValueError(opens in a new tab) – If the selected mode is not supported.



A list of AncillaQubits in the order that they were added. You should not mutate this.


Return calibration dictionary.

The custom pulse definition of a given gate is of the form {'gate_name': {(qubits, params): schedule}}


A list of Clbits in the order that they were added. You should not mutate this.



Get the entanglement strategy.


The entanglement strategy, see get_entangler_map() for more detail on how the format is interpreted.


The blocks in the entanglement layers.


The blocks in the entanglement layers.


Returns whether the circuit is wrapped in nested gates/instructions or flattened.


The global phase of the current circuit scope in radians.


Return the initial state that is added in front of the n-local circuit.


The initial state.


If barriers are inserted in between the layers or not.


True, if barriers are inserted in between the layers, False if not.


Default value: 160


Return any associated layout information about the circuit

This attribute contains an optional TranspileLayout object. This is typically set on the output from transpile() or to retain information about the permutations caused on the input circuit by transpilation.

There are two types of permutations caused by the transpile() function, an initial layout which permutes the qubits based on the selected physical qubits on the Target, and a final layout which is an output permutation caused by SwapGates inserted during routing.


Arbitrary user-defined metadata for the circuit.

Qiskit will not examine the content of this mapping, but it will pass it through the transpiler and reattach it to the output, so you can track your own metadata.


Return the number of ancilla qubits.


The number of real-time classical variables in the circuit marked as captured from an enclosing scope.

This is the length of the iter_captured_vars() iterable. If this is non-zero, num_input_vars must be zero.


Return number of classical bits.


The number of real-time classical variables in the circuit that are declared by this circuit scope, excluding inputs or captures.

This is the length of the iter_declared_vars() iterable.


The number of real-time classical variables in the circuit marked as circuit inputs.

This is the length of the iter_input_vars() iterable. If this is non-zero, num_captured_vars must be zero.


Return the number of layers in the n-local circuit.


The number of layers in the circuit.



The number of total parameters that can be set to distinct values.

This does not change when the parameters are bound or exchanged for same parameters, and therefore is different from num_parameters which counts the number of unique Parameter objects currently in the circuit.


The number of parameters originally available in the circuit.


This quantity does not require the circuit to be built yet.


Returns the number of qubits in this circuit.


The number of qubits.


The number of real-time classical variables in the circuit.

This is the length of the iter_vars() iterable.


Return a list of operation start times.

This attribute is enabled once one of scheduling analysis passes runs on the quantum circuit.


List of integers representing instruction start times. The index corresponds to the index of instruction in


AttributeError(opens in a new tab) – When circuit is not scheduled.


The parameters used in the underlying circuit.

This includes float values and duplicates.


>>> # prepare circuit ...
>>> print(nlocal)
q_0:Ry(1) ├┤ Ry(θ[1]) ├┤ Ry(θ[1]) ├┤ Ry(θ[3])
>>> nlocal.parameters
{Parameter(θ[1]), Parameter(θ[3])}
>>> nlocal.ordered_parameters
[1, Parameter(θ[1]), Parameter(θ[1]), Parameter(θ[3])]


The parameters objects used in the circuit.


Return the parameter bounds.


The parameter bounds.



The initial points for the parameters. Can be stored as initial guess in optimization.


The initial values for the parameters, or None, if none have been set.


Default value: 'circuit'


Type: list[QuantumRegister]

A list of the QuantumRegisters in this circuit. You should not mutate this.


A list of Qubits in the order that they were added. You should not mutate this.


The number of times rotation and entanglement block are repeated.


The number of repetitions.


The blocks in the rotation layers.


The blocks in the rotation layers.


Type: str

A human-readable name for the circuit.


Type: list[ClassicalRegister]

A list of the ClassicalRegisters in this circuit. You should not mutate this.


Type: int | float | None

The total duration of the circuit, set by a scheduling transpiler pass. Its unit is specified by unit.


The unit that duration is specified in.

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