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)[source]¶
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 \(Y\) rotations and \(CX\) entanglements. The entanglement pattern can be user-defined or selected from a predefined set. It is calledRealAmplitudes
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 ofTwoLocal
andNLocal
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 \(Y\) rotations can be reduced to a single \(Y\) 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
TwoLocal
for 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
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 toTrue
to 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.
- extension_lib = 'include "qelib1.inc";'¶
- 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.
- header = 'OPENQASM 2.0;'¶
- 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 = 159¶
- layout¶
Return any associated layout information about the circuit
This attribute contains an optional
TranspileLayout
object. This is typically set on the output fromtranspile()
orPassManager.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 theTarget
, and a final layout which is an output permutation caused bySwapGate
s 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 uniqueParameter
objects currently in the circuit.- Returns:
The number of parameters originally available in the circuit.
Note
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 = 'circuit'¶
- qregs: 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.