TwoLocal
class qiskit.circuit.library.TwoLocal(num_qubits=None, rotation_blocks=None, entanglement_blocks=None, entanglement='full', reps=3, skip_unentangled_qubits=False, skip_final_rotation_layer=False, parameter_prefix='θ', insert_barriers=False, initial_state=None, name='TwoLocal', flatten=None)
Bases: NLocal
The two-local circuit.
The two-local circuit is a parameterized circuit consisting of alternating rotation layers and entanglement layers. The rotation layers are single qubit gates applied on all qubits. The entanglement layer uses two-qubit gates to entangle the qubits according to a strategy set using entanglement
. Both the rotation and entanglement gates can be specified as string (e.g. 'ry'
or 'cx'
), as gate-type (e.g. RYGate
or CXGate
) or as QuantumCircuit (e.g. a 1-qubit circuit or 2-qubit circuit).
A set of default entanglement strategies is provided:
'full'
entanglement is each qubit is entangled with all the others.'linear'
entanglement is qubit entangled with qubit , for all , where is the total number of qubits.'reverse_linear'
entanglement is qubit entangled with qubit , for all , where is the total number of qubits. Note that ifentanglement_blocks = 'cx'
then this option provides the same unitary as'full'
with fewer entangling gates.'pairwise'
entanglement is one layer where qubit is entangled with qubit , for all even values of , and then a second layer where qubit is entangled with qubit , for all odd values of .'circular'
entanglement is linear entanglement but with an additional entanglement of the first and last qubit before the linear part.'sca'
(shifted-circular-alternating) entanglement is a generalized and modified version of the proposed circuit 14 in Sim et al.. It consists of circular entanglement where the ‘long’ entanglement connecting the first with the last qubit is shifted by one each block. Furthermore the role of control and target qubits are swapped every block (therefore alternating).
The entanglement can further be specified using an entangler map, which is a list of index pairs, such as
>>> entangler_map = [(0, 1), (1, 2), (2, 0)]
If different entanglements per block should be used, provide a list of entangler maps. See the examples below on how this can be used.
>>> entanglement = [entangler_map_layer_1, entangler_map_layer_2, ... ]
Barriers can be inserted in between the different layers for better visualization using the insert_barriers
attribute.
For each parameterized gate a new parameter is generated using a ParameterVector
. The name of these parameters can be chosen using the parameter_prefix
.
Examples
>>> two = TwoLocal(3, 'ry', 'cx', 'linear', reps=2, insert_barriers=True)
>>> print(two) # decompose the layers into standard gates
┌──────────┐ ░ ░ ┌──────────┐ ░ ░ ┌──────────┐
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]) ├
└──────────┘ ░ └───┘ ░ └──────────┘ ░ └───┘ ░ └──────────┘
>>> two = TwoLocal(3, ['ry','rz'], 'cz', 'full', reps=1, insert_barriers=True)
>>> qc = QuantumCircuit(3)
>>> qc &= two
>>> print(qc.decompose().draw())
┌──────────┐┌──────────┐ ░ ░ ┌──────────┐ ┌──────────┐
q_0: ┤ Ry(θ[0]) ├┤ Rz(θ[3]) ├─░──■──■─────░─┤ Ry(θ[6]) ├─┤ Rz(θ[9]) ├
├──────────┤├──────────┤ ░ │ │ ░ ├──────────┤┌┴──────────┤
q_1: ┤ Ry(θ[1]) ├┤ Rz(θ[4]) ├─░──■──┼──■──░─┤ Ry(θ[7]) ├┤ Rz(θ[10]) ├
├──────────┤├──────────┤ ░ │ │ ░ ├──────────┤├───────────┤
q_2: ┤ Ry(θ[2]) ├┤ Rz(θ[5]) ├─░─────■──■──░─┤ Ry(θ[8]) ├┤ Rz(θ[11]) ├
└──────────┘└──────────┘ ░ ░ └──────────┘└───────────┘
>>> entangler_map = [[0, 1], [1, 2], [2, 0]] # circular entanglement for 3 qubits
>>> two = TwoLocal(3, 'x', 'crx', entangler_map, reps=1)
>>> print(two) # note: no barriers inserted this time!
┌───┐ ┌──────────┐┌───┐
q_0: |0>┤ X ├─────■───────────────────────┤ Rx(θ[2]) ├┤ X ├
├───┤┌────┴─────┐ ┌───┐└─────┬────┘└───┘
q_1: |0>┤ X ├┤ Rx(θ[0]) ├─────■──────┤ X ├──────┼──────────
├───┤└──────────┘┌────┴─────┐└───┘ │ ┌───┐
q_2: |0>┤ X ├────────────┤ Rx(θ[1]) ├───────────■─────┤ X ├
└───┘ └──────────┘ └───┘
>>> entangler_map = [[0, 3], [0, 2]] # entangle the first and last two-way
>>> two = TwoLocal(4, [], 'cry', entangler_map, reps=1)
>>> circuit = two.compose(two)
>>> print(circuit.decompose().draw()) # note, that the parameters are the same!
q_0: ─────■───────────■───────────■───────────■──────
│ │ │ │
q_1: ─────┼───────────┼───────────┼───────────┼──────
│ ┌────┴─────┐ │ ┌────┴─────┐
q_2: ─────┼──────┤ Ry(θ[1]) ├─────┼──────┤ Ry(θ[1]) ├
┌────┴─────┐└──────────┘┌────┴─────┐└──────────┘
q_3: ┤ Ry(θ[0]) ├────────────┤ Ry(θ[0]) ├────────────
└──────────┘ └──────────┘
>>> layer_1 = [(0, 1), (0, 2)]
>>> layer_2 = [(1, 2)]
>>> two = TwoLocal(3, 'x', 'cx', [layer_1, layer_2], reps=2, insert_barriers=True)
>>> print(two)
┌───┐ ░ ░ ┌───┐ ░ ░ ┌───┐
q_0: ┤ X ├─░───■────■───░─┤ X ├─░───────░─┤ X ├
├───┤ ░ ┌─┴─┐ │ ░ ├───┤ ░ ░ ├───┤
q_1: ┤ X ├─░─┤ X ├──┼───░─┤ X ├─░───■───░─┤ X ├
├───┤ ░ └───┘┌─┴─┐ ░ ├───┤ ░ ┌─┴─┐ ░ ├───┤
q_2: ┤ X ├─░──────┤ X ├─░─┤ X ├─░─┤ X ├─░─┤ X ├
└───┘ ░ └───┘ ░ └───┘ ░ └───┘ ░ └───┘
Parameters
- num_qubits (int | None) – The number of qubits of the two-local circuit.
- rotation_blocks (str |type |qiskit.circuit.Instruction |QuantumCircuit |list[str |type |qiskit.circuit.Instruction |QuantumCircuit] | None) – The gates used in the rotation layer. Can be specified via the name of a gate (e.g.
'ry'
) or the gate type itself (e.g.RYGate
). If only one gate is provided, the gate same gate is applied to each qubit. If a list of gates is provided, all gates are applied to each qubit in the provided order. See the Examples section for more detail. - entanglement_blocks (str |type |qiskit.circuit.Instruction |QuantumCircuit |list[str |type |qiskit.circuit.Instruction |QuantumCircuit] | None) – The gates used in the entanglement layer. Can be specified in the same format as
rotation_blocks
. - 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'full'
entanglement. Note that ifentanglement_blocks = 'cx'
, then'full'
entanglement provides the same unitary as'reverse_linear'
but the latter option has fewer entangling gates. See the Examples section for more detail. - reps (int) – Specifies how often a block consisting of a rotation layer and entanglement layer is repeated.
- skip_unentangled_qubits (bool) – If
True
, the single qubit gates are only applied to qubits that are entangled with another qubit. IfFalse
, the single qubit gates are applied to each qubit in the ansatz. Defaults toFalse
. - skip_final_rotation_layer (bool) – If
False
, a rotation layer is added at the end of the ansatz. IfTrue
, no rotation layer is added. - parameter_prefix (str) – The parameterized gates require a parameter to be defined, for which we use instances of
Parameter
. The name of each parameter will be this specified prefix plus its index. - insert_barriers (bool) – If
True
, barriers are inserted in between each layer. IfFalse
, no barriers are inserted. Defaults toFalse
. - initial_state (QuantumCircuit | None) – A
QuantumCircuit
object to prepend to the circuit. - 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
A list of AncillaQubit
s in the order that they were added. You should not mutate this.
calibrations
Return calibration dictionary.
The custom pulse definition of a given gate is of the form {'gate_name': {(qubits, params): schedule}}
clbits
A list of Clbit
s in the order that they were added. You should not mutate this.
data
The circuit data (instructions and context).
Returns
a list-like object containing the CircuitInstruction
s for each instruction.
Return type
QuantumCircuitData
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
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: 186
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 SwapGate
s inserted during routing.
metadata
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.
num_ancillas
Return the number of ancilla qubits.
num_captured_vars
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.
num_clbits
Return number of classical bits.
num_declared_vars
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.
num_input_vars
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.
num_layers
Return the number of layers in the n-local circuit.
Returns
The number of layers in the circuit.
num_parameters
The number of parameter objects in the circuit.
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.
num_vars
The number of real-time classical variables in the circuit.
This is the length of the iter_vars()
iterable.
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
The parameter bounds for the unbound parameters in the circuit.
Returns
A list of pairs indicating the bounds, as (lower, upper). None indicates an unbounded parameter in the corresponding direction. If None
is returned, problem is fully unbounded.
parameters
The parameters defined in the circuit.
This attribute returns the Parameter
objects in the circuit sorted alphabetically. Note that parameters instantiated with a ParameterVector
are still sorted numerically.
Examples
The snippet below shows that insertion order of parameters does not matter.
>>> from qiskit.circuit import QuantumCircuit, Parameter
>>> a, b, elephant = Parameter("a"), Parameter("b"), Parameter("elephant")
>>> circuit = QuantumCircuit(1)
>>> circuit.rx(b, 0)
>>> circuit.rz(elephant, 0)
>>> circuit.ry(a, 0)
>>> circuit.parameters # sorted alphabetically!
ParameterView([Parameter(a), Parameter(b), Parameter(elephant)])
Bear in mind that alphabetical sorting might be unintuitive when it comes to numbers. The literal “10” comes before “2” in strict alphabetical sorting.
>>> from qiskit.circuit import QuantumCircuit, Parameter
>>> angles = [Parameter("angle_1"), Parameter("angle_2"), Parameter("angle_10")]
>>> circuit = QuantumCircuit(1)
>>> circuit.u(*angles, 0)
>>> circuit.draw()
┌─────────────────────────────┐
q: ┤ U(angle_1,angle_2,angle_10) ├
└─────────────────────────────┘
>>> circuit.parameters
ParameterView([Parameter(angle_1), Parameter(angle_10), Parameter(angle_2)])
To respect numerical sorting, a ParameterVector
can be used.
>>> from qiskit.circuit import QuantumCircuit, Parameter, ParameterVector
>>> x = ParameterVector("x", 12)
>>> circuit = QuantumCircuit(1)
>>> for x_i in x:
... circuit.rx(x_i, 0)
>>> circuit.parameters
ParameterView([
ParameterVectorElement(x[0]), ParameterVectorElement(x[1]),
ParameterVectorElement(x[2]), ParameterVectorElement(x[3]),
..., ParameterVectorElement(x[11])
])
Returns
The sorted Parameter
objects in the circuit.
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 QuantumRegister
s in this circuit. You should not mutate this.
qubits
A list of Qubit
s in the order that they were added. You should not mutate this.
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.
name
Type: str
A human-readable name for the circuit.
cregs
Type: list[ClassicalRegister]
A list of the ClassicalRegister
s in this circuit. You should not mutate this.
duration
Type: int | float | None
The total duration of the circuit, set by a scheduling transpiler pass. Its unit is specified by unit
.
unit
The unit that duration
is specified in.
Methods
get_entangler_map
get_entangler_map(rep_num, block_num, num_block_qubits)
Overloading to handle the special case of 1 qubit where the entanglement are ignored.
Return type