RealAmplitudes
class qiskit.circuit.library.RealAmplitudes(num_qubits=None, entanglement='reverse_linear', reps=3, skip_unentangled_qubits=False, skip_final_rotation_layer=False, parameter_prefix='θ', insert_barriers=False, initial_state=None, name='RealAmplitudes', flatten=None)
Bases: TwoLocal
The real-amplitudes 2-local circuit.
The RealAmplitudes circuit is a heuristic trial wave function used as Ansatz in chemistry applications or classification circuits in machine learning. The circuit consists of alternating layers of rotations and entanglements. The entanglement pattern can be user-defined or selected from a predefined set. It is called RealAmplitudes since the prepared quantum states will only have real amplitudes, the complex part is always 0.
For example a RealAmplitudes circuit with 2 repetitions on 3 qubits with 'reverse_linear' entanglement is
┌──────────┐ ░ ░ ┌──────────┐ ░ ░ ┌──────────┐
┤ Ry(θ[0]) ├─░────────■───░─┤ Ry(θ[3]) ├─░────────■───░─┤ Ry(θ[6]) ├
├──────────┤ ░ ┌─┴─┐ ░ ├──────────┤ ░ ┌─┴─┐ ░ ├──────────┤
┤ Ry(θ[1]) ├─░───■──┤ X ├─░─┤ Ry(θ[4]) ├─░───■──┤ X ├─░─┤ Ry(θ[7]) ├
├──────────┤ ░ ┌─┴─┐└───┘ ░ ├──────────┤ ░ ┌─┴─┐└───┘ ░ ├──────────┤
┤ Ry(θ[2]) ├─░─┤ X ├──────░─┤ Ry(θ[5]) ├─░─┤ X ├──────░─┤ Ry(θ[8]) ├
└──────────┘ ░ └───┘ ░ └──────────┘ ░ └───┘ ░ └──────────┘The entanglement can be set using the entanglement keyword as string or a list of index-pairs. See the documentation of TwoLocal and NLocal for more detail. Additional options that can be set include the number of repetitions, skipping rotation gates on qubits that are not entangled, leaving out the final rotation layer and inserting barriers in between the rotation and entanglement layers.
If some qubits are not entangled with other qubits it makes sense to not apply rotation gates on these qubits, since a sequence of rotations can be reduced to a single rotation with summed rotation angles.
Examples
>>> ansatz = RealAmplitudes(3, reps=2) # create the circuit on 3 qubits
>>> print(ansatz)
┌──────────┐ ┌──────────┐ ┌──────────┐
q_0: ┤ Ry(θ[0]) ├──────────■──────┤ Ry(θ[3]) ├──────────■──────┤ Ry(θ[6]) ├
├──────────┤ ┌─┴─┐ ├──────────┤ ┌─┴─┐ ├──────────┤
q_1: ┤ Ry(θ[1]) ├──■─────┤ X ├────┤ Ry(θ[4]) ├──■─────┤ X ├────┤ Ry(θ[7]) ├
├──────────┤┌─┴─┐┌──┴───┴───┐└──────────┘┌─┴─┐┌──┴───┴───┐└──────────┘
q_2: ┤ Ry(θ[2]) ├┤ X ├┤ Ry(θ[5]) ├────────────┤ X ├┤ Ry(θ[8]) ├────────────
└──────────┘└───┘└──────────┘ └───┘└──────────┘>>> ansatz = RealAmplitudes(3, entanglement='full', reps=2) # it is the same unitary as above
>>> print(ansatz)
┌──────────┐ ┌──────────┐ ┌──────────┐
q_0: ┤ RY(θ[0]) ├──■────■──┤ RY(θ[3]) ├──────────────■────■──┤ RY(θ[6]) ├────────────
├──────────┤┌─┴─┐ │ └──────────┘┌──────────┐┌─┴─┐ │ └──────────┘┌──────────┐
q_1: ┤ RY(θ[1]) ├┤ X ├──┼───────■──────┤ RY(θ[4]) ├┤ X ├──┼───────■──────┤ RY(θ[7]) ├
├──────────┤└───┘┌─┴─┐ ┌─┴─┐ ├──────────┤└───┘┌─┴─┐ ┌─┴─┐ ├──────────┤
q_2: ┤ RY(θ[2]) ├─────┤ X ├───┤ X ├────┤ RY(θ[5]) ├─────┤ X ├───┤ X ├────┤ RY(θ[8]) ├
└──────────┘ └───┘ └───┘ └──────────┘ └───┘ └───┘ └──────────┘>>> ansatz = RealAmplitudes(3, entanglement='linear', reps=2, insert_barriers=True)
>>> qc = QuantumCircuit(3) # create a circuit and append the RY variational form
>>> qc.compose(ansatz, inplace=True)
>>> qc.draw()
┌──────────┐ ░ ░ ┌──────────┐ ░ ░ ┌──────────┐
q_0: ┤ RY(θ[0]) ├─░───■────────░─┤ RY(θ[3]) ├─░───■────────░─┤ RY(θ[6]) ├
├──────────┤ ░ ┌─┴─┐ ░ ├──────────┤ ░ ┌─┴─┐ ░ ├──────────┤
q_1: ┤ RY(θ[1]) ├─░─┤ X ├──■───░─┤ RY(θ[4]) ├─░─┤ X ├──■───░─┤ RY(θ[7]) ├
├──────────┤ ░ └───┘┌─┴─┐ ░ ├──────────┤ ░ └───┘┌─┴─┐ ░ ├──────────┤
q_2: ┤ RY(θ[2]) ├─░──────┤ X ├─░─┤ RY(θ[5]) ├─░──────┤ X ├─░─┤ RY(θ[8]) ├
└──────────┘ ░ └───┘ ░ └──────────┘ ░ └───┘ ░ └──────────┘>>> ansatz = RealAmplitudes(4, reps=1, entanglement='circular', insert_barriers=True)
>>> print(ansatz)
┌──────────┐ ░ ┌───┐ ░ ┌──────────┐
q_0: ┤ RY(θ[0]) ├─░─┤ X ├──■─────────────░─┤ RY(θ[4]) ├
├──────────┤ ░ └─┬─┘┌─┴─┐ ░ ├──────────┤
q_1: ┤ RY(θ[1]) ├─░───┼──┤ X ├──■────────░─┤ RY(θ[5]) ├
├──────────┤ ░ │ └───┘┌─┴─┐ ░ ├──────────┤
q_2: ┤ RY(θ[2]) ├─░───┼───────┤ X ├──■───░─┤ RY(θ[6]) ├
├──────────┤ ░ │ └───┘┌─┴─┐ ░ ├──────────┤
q_3: ┤ RY(θ[3]) ├─░───■────────────┤ X ├─░─┤ RY(θ[7]) ├
└──────────┘ ░ └───┘ ░ └──────────┘>>> ansatz = RealAmplitudes(4, reps=2, entanglement=[[0,3], [0,2]],
... skip_unentangled_qubits=True)
>>> print(ansatz)
┌──────────┐ ┌──────────┐ ┌──────────┐
q_0: ┤ RY(θ[0]) ├──■───────■──────┤ RY(θ[3]) ├──■───────■──────┤ RY(θ[6]) ├
└──────────┘ │ │ └──────────┘ │ │ └──────────┘
q_1: ──────────────┼───────┼────────────────────┼───────┼──────────────────
┌──────────┐ │ ┌─┴─┐ ┌──────────┐ │ ┌─┴─┐ ┌──────────┐
q_2: ┤ RY(θ[1]) ├──┼─────┤ X ├────┤ RY(θ[4]) ├──┼─────┤ X ├────┤ RY(θ[7]) ├
├──────────┤┌─┴─┐┌──┴───┴───┐└──────────┘┌─┴─┐┌──┴───┴───┐└──────────┘
q_3: ┤ RY(θ[2]) ├┤ X ├┤ RY(θ[5]) ├────────────┤ X ├┤ RY(θ[8]) ├────────────
└──────────┘└───┘└──────────┘ └───┘└──────────┘Parameters
- num_qubits (int | None) – The number of qubits of the RealAmplitudes circuit.
- reps (int) – Specifies how often the structure of a rotation layer followed by an entanglement layer is repeated.
- entanglement (str |list[list[int]] | Callable[[int], list[int]]) – Specifies the entanglement structure. Can be a string (‘full’, ‘linear’ ‘reverse_linear, ‘circular’ 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. Default to ‘reverse_linear’ entanglement. Note that ‘reverse_linear’ entanglement provides the same unitary as ‘full’ with fewer entangling gates. See the Examples section of
TwoLocalfor more detail. - initial_state (QuantumCircuit | None) – A QuantumCircuit object to prepend to the circuit.
- skip_unentangled_qubits (bool) – 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) – If False, a rotation layer is added at the end of the ansatz. If True, no rotation layer is added.
- parameter_prefix (str) – The parameterized gates require a parameter to be defined, for which we use
ParameterVector. - insert_barriers (bool) – If True, barriers are inserted in between each layer. If False, no barriers are inserted.
- flatten (bool | None) – Set this to
Trueto 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 toTrueto avoid a large performance overhead for parameter binding.
Attributes
ancillas
Returns a list of ancilla bits in the order that the registers were added.
calibrations
Return calibration dictionary.
The custom pulse definition of a given gate is of the form {'gate_name': {(qubits, params): schedule}}
clbits
Returns a list of classical bits in the order that the registers were added.
data
entanglement
Get the entanglement strategy.
Returns
The entanglement strategy, see get_entangler_map() for more detail on how the format is interpreted.
entanglement_blocks
The blocks in the entanglement layers.
Returns
The blocks in the entanglement layers.
flatten
Returns whether the circuit is wrapped in nested gates/instructions or flattened.
global_phase
Return the global phase of the current circuit scope in radians.
initial_state
Return the initial state that is added in front of the n-local circuit.
Returns
The initial state.
insert_barriers
If barriers are inserted in between the layers or not.
Returns
True, if barriers are inserted in between the layers, False if not.
instances
Default value: 412
layout
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 PassManager.run() 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.
metadata
The user provided metadata associated with the circuit.
The metadata for the circuit is a user provided dict of metadata for the circuit. It will not be used to influence the execution or operation of the circuit, but it is expected to be passed between all transforms of the circuit (ie transpilation) and that providers will associate any circuit metadata with the results it returns from execution of that circuit.
num_ancillas
Return the number of ancilla qubits.
num_clbits
Return number of classical bits.
num_layers
Return the number of layers in the n-local circuit.
Returns
The number of layers in the circuit.
num_parameters
num_parameters_settable
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.
Returns
The number of parameters originally available in the circuit.
This quantity does not require the circuit to be built yet.
num_qubits
Returns the number of qubits in this circuit.
Returns
The number of qubits.
op_start_times
Return a list of operation start times.
This attribute is enabled once one of scheduling analysis passes runs on the quantum circuit.
Returns
List of integers representing instruction start times. The index corresponds to the index of instruction in QuantumCircuit.data.
Raises
AttributeError – When circuit is not scheduled.
ordered_parameters
The parameters used in the underlying circuit.
This includes float values and duplicates.
Examples
>>> # 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])]Returns
The parameters objects used in the circuit.
parameter_bounds
Return the parameter bounds.
Returns
The parameter bounds.
parameters
preferred_init_points
The initial points for the parameters. Can be stored as initial guess in optimization.
Returns
The initial values for the parameters, or None, if none have been set.
prefix
Default value: 'circuit'
qregs
Type: list[QuantumRegister]
A list of the quantum registers associated with the circuit.
qubits
Returns a list of quantum bits in the order that the registers were added.
reps
The number of times rotation and entanglement block are repeated.
Returns
The number of repetitions.
rotation_blocks
The blocks in the rotation layers.
Returns
The blocks in the rotation layers.