ZZFeatureMap

class ZZFeatureMap(feature_dimension, reps=2, entanglement='full', data_map_func=None, insert_barriers=False)

Second-order Pauli-Z evolution circuit.

For 3 qubits and 1 repetition and linear entanglement the circuit is represented by:

┌───┐┌─────────────────┐
┤ H ├┤ U1(2.0*φ(x[0])) ├──■────────────────────────────■────────────────────────────────────
├───┤├─────────────────┤┌─┴─┐┌──────────────────────┐┌─┴─┐
┤ H ├┤ U1(2.0*φ(x[1])) ├┤ X ├┤ U1(2.0*φ(x[0],x[1])) ├┤ X ├──■────────────────────────────■──
├───┤├─────────────────┤└───┘└──────────────────────┘└───┘┌─┴─┐┌──────────────────────┐┌─┴─┐
┤ H ├┤ U1(2.0*φ(x[2])) ├──────────────────────────────────┤ X ├┤ U1(2.0*φ(x[1],x[2])) ├┤ X ├
└───┘└─────────────────┘                                  └───┘└──────────────────────┘└───┘

where φ is a classical non-linear function, which defaults to φ(x) = x if and φ(x,y) = (pi - x)(pi - y).

Examples

>>> prep = ZZFeatureMap(2, reps=2)
>>> print(prep)
     ┌───┐┌──────────────┐
q_0: ┤ H ├┤ U1(2.0*x[0]) ├──■───────────────────────────────────────■──
     ├───┤├──────────────┤┌─┴─┐┌─────────────────────────────────┐┌─┴─┐
q_1: ┤ H ├┤ U1(2.0*x[1]) ├┤ X ├┤ U1(2.0*(pi - x[0])*(pi - x[1])) ├┤ X ├
     └───┘└──────────────┘└───┘└─────────────────────────────────┘└───┘

>>> from qiskit.circuit.library import EfficientSU2
>>> classifier = ZZFeatureMap(3) + EfficientSU2(3)
>>> classifier.num_parameters
15
>>> classifier.parameters  # 'x' for the data preparation, 'θ' for the SU2 parameters
{Parameter(θ[9]), Parameter(θ[4]), Parameter(θ[6]), Parameter(θ[1]), Parameter(x[2]),
Parameter(θ[7]), Parameter(x[1]), Parameter(θ[8]), Parameter(θ[2]), Parameter(θ[10]),
Parameter(θ[5]), Parameter(θ[0]), Parameter(θ[3]), Parameter(x[0]), Parameter(θ[11])}
>>> classifier.count_ops()
OrderedDict([('u1', 12), ('cx', 12), ('ry', 12), ('cz', 9), ('h', 6)])

Create a new second-order Pauli-Z expansion.

Parameters

feature_dimension (int) – Number of features.
reps (int) – The number of repeated circuits, has a min. value of 1.
entanglement (Union[str, List[List[int]], Callable[[int], List[int]]]) – Specifies the entanglement structure. Refer to NLocal for detail.
data_map_func (Optional[Callable[[ndarray], float]]) – A mapping function for data x.
insert_barriers (bool) – If True, barriers are inserted in between the evolution instructions and hadamard layers.

Attributes

clbits

Returns a list of classical bits in the order that the registers were added.

data

Return the circuit data (instructions and context).

Returns

a list-like object containing the tuples for the circuit’s data.

Each tuple is in the format (instruction, qargs, cargs), where instruction is an Instruction (or subclass) object, qargs is a list of Qubit objects, and cargs is a list of Clbit objects.

Return type

QuantumCircuitData

entanglement

Type: Union[str, List[str], List[List[str]], List[int], List[List[int]], List[List[List[int]]], List[List[List[List[int]]]], Callable[[int], str], Callable[[int], List[List[int]]]]

Get the entanglement strategy.

Return type

Union[str, List[str], List[List[str]], List[int], List[List[int]], List[List[List[int]]], List[List[List[List[int]]]], Callable[[int], str], Callable[[int], List[List[int]]]]

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

Default value: 'include "qelib1.inc";'

feature_dimension

Type: int

Returns the feature dimension (which is equal to the number of qubits).

Return type

int

Returns

The feature dimension of this feature map.

header

Default value: 'OPENQASM 2.0;'

initial_state

Type: Any

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

Return type

Any

Returns

The initial state.

insert_barriers

Type: bool

If barriers are inserted in between the layers or not.

Return type

bool

Returns

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

instances

Default value: 8

n_qubits

Deprecated, use num_qubits instead. Return number of qubits.

num_clbits

Return number of classical bits.

num_layers

Type: int

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

Return type

int

Returns

The number of layers in the circuit.

num_parameters

Convenience function to get the number of parameter objects in the circuit.

num_parameters_settable

The number of distinct parameters.

num_qubits

Type: int

Returns the number of qubits in this circuit.

Return type

int

Returns

The number of qubits.

ordered_parameters

Type: List[qiskit.circuit.parameter.Parameter]

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])]

Return type

List[Parameter]

Returns

The parameters objects used in the circuit.

parameter_bounds

Type: Optional[List[Tuple[float, float]]]

The parameter bounds for the unbound parameters in the circuit.

Return type

Optional[List[Tuple[float, float]]]

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

Type: Set[qiskit.circuit.parameter.Parameter]

Get the Parameter objects in the circuit.

Return type

Set[Parameter]

Returns

A set containing the unbound circuit parameters.

paulis

Type: List[str]

The Pauli strings used in the entanglement of the qubits.

Return type

List[str]

Returns

The Pauli strings as list.

preferred_init_points

Type: Optional[List[float]]

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

Return type

Optional[List[float]]

Returns

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

prefix

Default value: 'circuit'

qregs

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

Type: int

The number of times rotation and entanglement block are repeated.

Return type

int

Returns

The number of repetitions.

rotation_blocks

Type: List[qiskit.circuit.instruction.Instruction]

The blocks in the rotation layers.

Return type

List[Instruction]

Returns

The blocks in the rotation layers.

Methods

AND

ZZFeatureMap.AND(qr_variables, qb_target, qr_ancillae, flags=None, mct_mode='no-ancilla')

Build a collective conjunction (AND) circuit in place using mct.

Parameters

self (QuantumCircuit) – The QuantumCircuit object to build the conjunction on.
qr_variables (QuantumRegister) – The QuantumRegister holding the variable qubits.
qb_target (Qubit) – The target qubit to hold the conjunction result.
qr_ancillae (QuantumRegister) – The ancillary QuantumRegister for building the mct.
flags (list[int]) – A list of +1/-1/0 to mark negations or omissions of qubits.
mct_mode (str) – The mct building mode.

OR

ZZFeatureMap.OR(qr_variables, qb_target, qr_ancillae, flags=None, mct_mode='basic')

Build a collective disjunction (OR) circuit in place using mct.

Parameters

self (QuantumCircuit) – The QuantumCircuit object to build the disjunction on.
qr_variables (QuantumRegister) – The QuantumRegister holding the variable qubits.
flags (list[int]) – A list of +1/-1/0 to mark negations or omissions of qubits.
qb_target (Qubit) – The target qubit to hold the disjunction result.
qr_ancillae (QuantumRegister) – The ancillary QuantumRegister for building the mct.
mct_mode (str) – The mct building mode.

getitem

ZZFeatureMap.__getitem__(item)

Return indexed operation.

len

ZZFeatureMap.__len__()

Return number of operations in circuit.

add_layer

ZZFeatureMap.add_layer(other, entanglement=None, front=False)

Append another layer to the NLocal.

Parameters

other (Union[NLocal, Instruction, QuantumCircuit]) – The layer to compose, can be another NLocal, an Instruction or Gate, or a QuantumCircuit.
entanglement (Union[List[int], str, List[List[int]], None]) – The entanglement or qubit indices.
front (bool) – If True, other is appended to the front, else to the back.

Return type

NLocal

Returns

self, such that chained composes are possible.

Raises

TypeError – If other is not compatible, i.e. is no Instruction and does not have a to_instruction method.

add_register

ZZFeatureMap.add_register(*regs)

Add registers.

append

ZZFeatureMap.append(instruction, qargs=None, cargs=None)

Append one or more instructions to the end of the circuit, modifying the circuit in place. Expands qargs and cargs.

Parameters

instruction (qiskit.circuit.Instruction) – Instruction instance to append
qargs (list(argument)) – qubits to attach instruction to
cargs (list(argument)) – clbits to attach instruction to

Returns

a handle to the instruction that was just added

Return type

qiskit.circuit.Instruction

assign_parameters

ZZFeatureMap.assign_parameters(param_dict, inplace=False)

Assign parameters to the n-local circuit.

This method also supports passing a list instead of a dictionary. If a list is passed, the list must have the same length as the number of unbound parameters in the circuit. The parameters are assigned in the order of the parameters in ordered_parameters().

Return type

Optional[QuantumCircuit]

Returns

A copy of the NLocal circuit with the specified parameters.

Raises

AttributeError – If the parameters are given as list and do not match the number of parameters.

barrier

ZZFeatureMap.barrier(*qargs)

Apply Barrier. If qargs is None, applies to all.

bind_parameters

ZZFeatureMap.bind_parameters(value_dict)

Assign numeric parameters to values yielding a new circuit.

To assign new Parameter objects or bind the values in-place, without yielding a new circuit, use the assign_parameters method.

Parameters

value_dict (dict) – {parameter: value, …}

Raises

CircuitError – If value_dict contains parameters not present in the circuit
TypeError – If value_dict contains a ParameterExpression in the values.

Returns

copy of self with assignment substitution.

Return type

QuantumCircuit

cast

static ZZFeatureMap.cast(value, _type)

Best effort to cast value to type. Otherwise, returns the value.

cbit_argument_conversion

ZZFeatureMap.cbit_argument_conversion(clbit_representation)

Converts several classical bit representations (such as indexes, range, etc.) into a list of classical bits.

Parameters

clbit_representation (Object) – representation to expand

Returns

Where each tuple is a classical bit.

Return type

List(tuple)

ccx

ZZFeatureMap.ccx(control_qubit1, control_qubit2, target_qubit, *, ctl1=None, ctl2=None, tgt=None)

Apply CCXGate.

ch

ZZFeatureMap.ch(control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CHGate.

cls_instances

classmethod ZZFeatureMap.cls_instances()

Return the current number of instances of this class, useful for auto naming.

cls_prefix

classmethod ZZFeatureMap.cls_prefix()

Return the prefix to use for auto naming.

cnot

ZZFeatureMap.cnot(control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CXGate.

combine

ZZFeatureMap.combine(rhs)

Append rhs to self if self contains compatible registers.

Two circuits are compatible if they contain the same registers or if they contain different registers with unique names. The returned circuit will contain all unique registers between both circuits.

Return self + rhs as a new object.

Parameters

rhs (QuantumCircuit) – The quantum circuit to append to the right hand side.

Returns

Returns a new QuantumCircuit object

Return type

QuantumCircuit

Raises

QiskitError – if the rhs circuit is not compatible

compose

ZZFeatureMap.compose(other, qubits=None, clbits=None, front=False, inplace=False)

Compose circuit with other circuit or instruction, optionally permuting wires.

other can be narrower or of equal width to self.

Parameters

other (qiskit.circuit.Instruction orQuantumCircuit or BaseOperator) – (sub)circuit to compose onto self.
qubits (list[Qubit|int]) – qubits of self to compose onto.
clbits (list[Clbit|int]) – clbits of self to compose onto.
front (bool) – If True, front composition will be performed (not implemented yet).
inplace (bool) – If True, modify the object. Otherwise return composed circuit.

Returns

the composed circuit (returns None if inplace==True).

Return type

QuantumCircuit

Raises

CircuitError – if composing on the front.
QiskitError – if other is wider or there are duplicate edge mappings.

Examples

>>> lhs.compose(rhs, qubits=[3, 2], inplace=True)

            ┌───┐                   ┌─────┐                ┌───┐
lqr_1_0: ───┤ H ├───    rqr_0: ──■──┤ Tdg ├    lqr_1_0: ───┤ H ├───────────────
            ├───┤              ┌─┴─┐└─────┘                ├───┤
lqr_1_1: ───┤ X ├───    rqr_1: ┤ X ├───────    lqr_1_1: ───┤ X ├───────────────
         ┌──┴───┴──┐           └───┘                    ┌──┴───┴──┐┌───┐
lqr_1_2: ┤ U1(0.1) ├  +                     =  lqr_1_2: ┤ U1(0.1) ├┤ X ├───────
         └─────────┘                                    └─────────┘└─┬─┘┌─────┐
lqr_2_0: ─────■─────                           lqr_2_0: ─────■───────■──┤ Tdg ├
            ┌─┴─┐                                          ┌─┴─┐        └─────┘
lqr_2_1: ───┤ X ├───                           lqr_2_1: ───┤ X ├───────────────
            └───┘                                          └───┘
lcr_0: 0 ═══════════                           lcr_0: 0 ═══════════════════════
 
lcr_1: 0 ═══════════                           lcr_1: 0 ═══════════════════════

copy

ZZFeatureMap.copy(name=None)

Copy the circuit.

Parameters

name (str) – name to be given to the copied circuit. If None, then the name stays the same

Returns

a deepcopy of the current circuit, with the specified name

Return type

QuantumCircuit

count_ops

ZZFeatureMap.count_ops()

Count each operation kind in the circuit.

Returns

a breakdown of how many operations of each kind, sorted by amount.

Return type

OrderedDict

crx

ZZFeatureMap.crx(theta, control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CRXGate.

cry

ZZFeatureMap.cry(theta, control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CRYGate.

crz

ZZFeatureMap.crz(theta, control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CRZGate.

cswap

ZZFeatureMap.cswap(control_qubit, target_qubit1, target_qubit2, *, label=None, ctrl_state=None, ctl=None, tgt1=None, tgt2=None)

Apply CSwapGate.

cu1

ZZFeatureMap.cu1(theta, control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CU1Gate.

cu3

ZZFeatureMap.cu3(theta, phi, lam, control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CU3Gate.

cx

ZZFeatureMap.cx(control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CXGate.

cy

ZZFeatureMap.cy(control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CYGate.

cz

ZZFeatureMap.cz(control_qubit, target_qubit, *, label=None, ctrl_state=None, ctl=None, tgt=None)

Apply CZGate.

dcx

ZZFeatureMap.dcx(qubit1, qubit2)

Apply DCXGate.

decompose

ZZFeatureMap.decompose()

Call a decomposition pass on this circuit, to decompose one level (shallow decompose).

Returns

a circuit one level decomposed

Return type

QuantumCircuit

depth

ZZFeatureMap.depth()

Return circuit depth (i.e., length of critical path). This does not include compiler or simulator directives such as ‘barrier’ or ‘snapshot’.

Returns

Depth of circuit.

Return type

int

Notes

The circuit depth and the DAG depth need not be the same.

diag_gate

ZZFeatureMap.diag_gate(diag, qubit)

Deprecated version of QuantumCircuit.diagonal.

diagonal

ZZFeatureMap.diagonal(diag, qubit)

Attach a diagonal gate to a circuit.

The decomposition is based on Theorem 7 given in “Synthesis of Quantum Logic Circuits” by Shende et al. (https://arxiv.org/pdf/quant-ph/0406176.pdf).

Parameters

diag (list) – list of the 2^k diagonal entries (for a diagonal gate on k qubits). Must contain at least two entries
qubit (QuantumRegister|list) – list of k qubits the diagonal is acting on (the order of the qubits specifies the computational basis in which the diagonal gate is provided: the first element in diag acts on the state where all the qubits in q are in the state 0, the second entry acts on the state where all the qubits q[1],…,q[k-1] are in the state zero and q[0] is in the state 1, and so on)

Returns

the diagonal gate which was attached to the circuit.

Return type

QuantumCircuit

Raises

QiskitError – if the list of the diagonal entries or the qubit list is in bad format; if the number of diagonal entries is not 2^k, where k denotes the number of qubits

draw

ZZFeatureMap.draw(output=None, scale=0.7, filename=None, style=None, interactive=False, line_length=None, plot_barriers=True, reverse_bits=False, justify=None, vertical_compression='medium', idle_wires=True, with_layout=True, fold=None, ax=None, initial_state=False, cregbundle=False)

Draw the quantum circuit.

text: ASCII art TextDrawing that can be printed in the console.

latex: high-quality images compiled via LaTeX.

latex_source: raw uncompiled LaTeX output.

matplotlib: images with color rendered purely in Python.

Parameters

output (str) – Select the output method to use for drawing the circuit. Valid choices are text, latex, latex_source, or mpl. By default the ‘text’ drawer is used unless a user config file has an alternative backend set as the default. If the output kwarg is set, that backend will always be used over the default in a user config file.
scale (float) – scale of image to draw (shrink if < 1)
filename (str) – file path to save image to
style (dict or str) – dictionary of style or file name of style file. This option is only used by the mpl output type. If a str is passed in that is the path to a json file which contains a dictionary of style, then that will be opened, parsed, and used as the input dict. See: Style Dict Doc for more information on the contents.
interactive (bool) – when set true show the circuit in a new window (for mpl this depends on the matplotlib backend being used supporting this). Note when used with either the text or the latex_source output type this has no effect and will be silently ignored.
line_length (int) – Deprecated; see fold which supersedes this option. Sets the length of the lines generated by text output type. This is useful when the drawing does not fit in the console. If None (default), it will try to guess the console width using shutil.get_terminal_size(). However, if you’re running in jupyter, the default line length is set to 80 characters. If you don’t want pagination at all, set line_length=-1.
reverse_bits (bool) – When set to True, reverse the bit order inside registers for the output visualization.
plot_barriers (bool) – Enable/disable drawing barriers in the output circuit. Defaults to True.
justify (string) – Options are left, right or none. If anything else is supplied it defaults to left justified. It refers to where gates should be placed in the output circuit if there is an option. none results in each gate being placed in its own column.
vertical_compression (string) – high, medium or low. It merges the lines generated by the text output so the drawing will take less vertical room. Default is medium. Only used by the text output, will be silently ignored otherwise.
idle_wires (bool) – Include idle wires (wires with no circuit elements) in output visualization. Default is True.
with_layout (bool) – Include layout information, with labels on the physical layout. Default is True.
fold (int) – Sets pagination. It can be disabled using -1. In text, sets the length of the lines. This is useful when the drawing does not fit in the console. If None (default), it will try to guess the console width using shutil. get_terminal_size(). However, if running in jupyter, the default line length is set to 80 characters. In mpl is the number of (visual) layers before folding. Default is 25.
ax (matplotlib.axes.Axes) – An optional Axes object to be used for the visualization output. If none is specified, a new matplotlib Figure will be created and used. Additionally, if specified, there will be no returned Figure since it is redundant. This is only used when the output kwarg is set to use the mpl backend. It will be silently ignored with all other outputs.
initial_state (bool) – Optional. Adds |0> in the beginning of the wire. Only used by the text, latex and latex_source outputs. Default: False.
cregbundle (bool) – Optional. If set True bundle classical registers. Only used by the text output. Default: False.

Returns

PIL.Image or matplotlib.figure or str or TextDrawing:

PIL.Image (output=’latex’)

an in-memory representation of the image of the circuit diagram.
matplotlib.figure.Figure (output=’mpl’)

a matplotlib figure object for the circuit diagram.
str (output=’latex_source’)

The LaTeX source code for visualizing the circuit diagram.
TextDrawing (output=’text’)

A drawing that can be printed as ASCII art.

Raises

VisualizationError – when an invalid output method is selected
ImportError – when the output methods require non-installed libraries

Style Dict Details

The style dict kwarg contains numerous options that define the style of the output circuit visualization. The style dict is only used by the mpl output. The options available in the style dict are defined below:

Parameters

textcolor (str) – The color code to use for text. Defaults to ‘#000000’
subtextcolor (str) – The color code to use for subtext. Defaults to ‘#000000’
linecolor (str) – The color code to use for lines. Defaults to ‘#000000’
creglinecolor (str) – The color code to use for classical register lines. Defaults to ‘#778899’
gatetextcolor (str) – The color code to use for gate text. Defaults to ‘#000000’
gatefacecolor (str) – The color code to use for gates. Defaults to ‘#ffffff’
barrierfacecolor (str) – The color code to use for barriers. Defaults to ‘#bdbdbd’
backgroundcolor (str) – The color code to use for the background. Defaults to ‘#ffffff’
fontsize (int) – The font size to use for text. Defaults to 13.
subfontsize (int) – The font size to use for subtext. Defaults to 8.

displaytext (dict) –

A dictionary of the text to use for each element type in the output visualization. The default values are:

{
    'id': 'id',
    'u0': 'U_0',
    'u1': 'U_1',
    'u2': 'U_2',
    'u3': 'U_3',
    'x': 'X',
    'y': 'Y',
    'z': 'Z',
    'h': 'H',
    's': 'S',
    'sdg': 'S^\dagger',
    't': 'T',
    'tdg': 'T^\dagger',
    'rx': 'R_x',
    'ry': 'R_y',
    'rz': 'R_z',
    'reset': '\left|0\right\rangle'
}

You must specify all the necessary values if using this. There is no provision for passing an incomplete dict in.

displaycolor (dict) –

The color codes to use for each circuit

element. The default values are:

{
    'id': '#F0E442',
    'u0': '#E7AB3B',
    'u1': '#E7AB3B',
    'u2': '#E7AB3B',
    'u3': '#E7AB3B',
    'x': '#58C698',
    'y': '#58C698',
    'z': '#58C698',
    'h': '#70B7EB',
    's': '#E0722D',
    'sdg': '#E0722D',
    't': '#E0722D',
    'tdg': '#E0722D',
    'rx': '#ffffff',
    'ry': '#ffffff',
    'rz': '#ffffff',
    'reset': '#D188B4',
    'target': '#70B7EB',
    'meas': '#D188B4'
}

Also, just like displaytext there is no provision for an incomplete dict passed in.

latexdrawerstyle (bool) – When set to True, enable LaTeX mode, which will draw gates like the latex output modes.
usepiformat (bool) – When set to True, use radians for output.
fold (int) – The number of circuit elements to fold the circuit at. Defaults to 20.
cregbundle (bool) – If set True, bundle classical registers
showindex (bool) – If set True, draw an index.
compress (bool) – If set True, draw a compressed circuit.
figwidth (int) – The maximum width (in inches) for the output figure.
dpi (int) – The DPI to use for the output image. Defaults to 150.
margin (list) – A list of margin values to adjust spacing around output image. Takes a list of 4 ints: [x left, x right, y bottom, y top].
creglinestyle (str) – The style of line to use for classical registers. Choices are ‘solid’, ‘doublet’, or any valid matplotlib linestyle kwarg value. Defaults to doublet

extend

ZZFeatureMap.extend(rhs)

Append QuantumCircuit to the right hand side if it contains compatible registers.

Two circuits are compatible if they contain the same registers or if they contain different registers with unique names. The returned circuit will contain all unique registers between both circuits.

Modify and return self.

Parameters

rhs (QuantumCircuit) – The quantum circuit to append to the right hand side.

Returns

Returns this QuantumCircuit object (which has been modified)

Return type

QuantumCircuit

Raises

QiskitError – if the rhs circuit is not compatible

fredkin

ZZFeatureMap.fredkin(control_qubit, target_qubit1, target_qubit2, *, ctl=None, tgt1=None, tgt2=None)

Apply CSwapGate.

from_qasm_file

static ZZFeatureMap.from_qasm_file(path)

Take in a QASM file and generate a QuantumCircuit object.

Parameters

path (str) – Path to the file for a QASM program

Returns

The QuantumCircuit object for the input QASM

Return type

QuantumCircuit

from_qasm_str

static ZZFeatureMap.from_qasm_str(qasm_str)

Take in a QASM string and generate a QuantumCircuit object.

Parameters

qasm_str (str) – A QASM program string

Returns

The QuantumCircuit object for the input QASM

Return type

QuantumCircuit

get_entangler_map

ZZFeatureMap.get_entangler_map(rep_num, block_num, num_block_qubits)

Get the entangler map for in the repetition rep_num and the block block_num.

The entangler map for the current block is derived from the value of self.entanglement. Below the different cases are listed, where i and j denote the repetition number and the block number, respectively, and n the number of qubits in the block.

entanglement type | entangler map ——————————-+——————————————————– None | [[0, …, n - 1]] str (e.g ‘full’) | the specified connectivity on n qubits List[int] | [entanglement] List[List[int]] | entanglement List[List[List[int]]] | entanglement[i] List[List[List[List[int]]]] | entanglement[i][j] List[str] | the connectivity specified in entanglement[i] List[List[str]] | the connectivity specified in entanglement[i][j] Callable[int, str] | same as List[str] Callable[int, List[List[int]]] | same as List[List[List[int]]]

Note that all indices are to be taken modulo the length of the array they act on, i.e. no out-of-bounds index error will be raised but we re-iterate from the beginning of the list.

Parameters

rep_num (int) – The current repetition we are in.
block_num (int) – The block number within the entanglement layers.
num_block_qubits (int) – The number of qubits in the block.

Return type

List[List[int]]

Returns

The entangler map for the current block in the current repetition.

Raises

ValueError – If the value of entanglement could not be cast to a corresponding entangler map.

get_unentangled_qubits

ZZFeatureMap.get_unentangled_qubits()

Get the indices of unentangled qubits in a set.

Return type

Set[int]

Returns

The unentangled qubits.

h

ZZFeatureMap.h(qubit, *, q=None)

Apply HGate.

hamiltonian

ZZFeatureMap.hamiltonian(operator, time, qubits, label=None)

Apply hamiltonian evolution to to qubits.

has_register

ZZFeatureMap.has_register(register)

Test if this circuit has the register r.

Parameters

register (Register) – a quantum or classical register.

Returns

True if the register is contained in this circuit.

Return type

bool

i

ZZFeatureMap.i(qubit, *, q=None)

Apply IGate.

id

ZZFeatureMap.id(qubit, *, q=None)

Apply IGate.

iden

ZZFeatureMap.iden(qubit, *, q=None)

Deprecated identity gate.

initialize

ZZFeatureMap.initialize(params, qubits)

Apply initialize to circuit.

inverse

ZZFeatureMap.inverse()

Invert this circuit.

This is done by recursively inverting all gates.

Returns

the inverted circuit

Return type

QuantumCircuit

Raises

CircuitError – if the circuit cannot be inverted.

iso

ZZFeatureMap.iso(isometry, q_input, q_ancillas_for_output, q_ancillas_zero=None, q_ancillas_dirty=None)

Attach an arbitrary isometry from m to n qubits to a circuit. In particular, this allows to attach arbitrary unitaries on n qubits (m=n) or to prepare any state on n qubits (m=0). The decomposition used here was introduced by Iten et al. in https://arxiv.org/abs/1501.06911.

Parameters

isometry (ndarray) – an isometry from m to n qubits, i.e., a (complex) ndarray of dimension 2^n×2^m with orthonormal columns (given in the computational basis specified by the order of the ancillas and the input qubits, where the ancillas are considered to be more significant than the input qubits.).
q_input (QuantumRegister|list[Qubit]) – list of m qubits where the input to the isometry is fed in (empty list for state preparation).
q_ancillas_for_output (QuantumRegister|list[Qubit]) – list of n-m ancilla qubits that are used for the output of the isometry and which are assumed to start in the zero state. The qubits are listed with increasing significance.
q_ancillas_zero (QuantumRegister|list[Qubit]) – list of ancilla qubits which are assumed to start in the zero state. Default is q_ancillas_zero = None.
q_ancillas_dirty (QuantumRegister|list[Qubit]) – list of ancilla qubits which can start in an arbitrary state. Default is q_ancillas_dirty = None.

Returns

the isometry is attached to the quantum circuit.

Return type

QuantumCircuit

Raises

QiskitError – if the array is not an isometry of the correct size corresponding to the provided number of qubits.

isometry

ZZFeatureMap.isometry(isometry, q_input, q_ancillas_for_output, q_ancillas_zero=None, q_ancillas_dirty=None)

Parameters

isometry (ndarray) – an isometry from m to n qubits, i.e., a (complex) ndarray of dimension 2^n×2^m with orthonormal columns (given in the computational basis specified by the order of the ancillas and the input qubits, where the ancillas are considered to be more significant than the input qubits.).
q_input (QuantumRegister|list[Qubit]) – list of m qubits where the input to the isometry is fed in (empty list for state preparation).
q_ancillas_for_output (QuantumRegister|list[Qubit]) – list of n-m ancilla qubits that are used for the output of the isometry and which are assumed to start in the zero state. The qubits are listed with increasing significance.
q_ancillas_zero (QuantumRegister|list[Qubit]) – list of ancilla qubits which are assumed to start in the zero state. Default is q_ancillas_zero = None.
q_ancillas_dirty (QuantumRegister|list[Qubit]) – list of ancilla qubits which can start in an arbitrary state. Default is q_ancillas_dirty = None.

Returns

the isometry is attached to the quantum circuit.

Return type

QuantumCircuit

Raises

QiskitError – if the array is not an isometry of the correct size corresponding to the provided number of qubits.

iswap

ZZFeatureMap.iswap(qubit1, qubit2)

Apply iSwapGate.

mcmt

ZZFeatureMap.mcmt(gate, control_qubits, target_qubits, ancilla_qubits=None, mode='no-ancilla', *, single_control_gate_fun=None, q_controls=None, q_ancillae=None, q_targets=None)

Apply a multi-control, multi-target using a generic gate.

This can also be used to implement a generic multi-control gate, as the target could also be of length 1.

mcrx

ZZFeatureMap.mcrx(theta, q_controls, q_target, use_basis_gates=False)

Apply Multiple-Controlled X rotation gate

Parameters

self (QuantumCircuit) – The QuantumCircuit object to apply the mcrx gate on.
theta (float) – angle theta
q_controls (list(Qubit)) – The list of control qubits
q_target (Qubit) – The target qubit
use_basis_gates (bool) – use u1, u2, u3, cx, id

Raises

QiskitError – parameter errors

mcry

ZZFeatureMap.mcry(theta, q_controls, q_target, q_ancillae, mode='basic', use_basis_gates=False)

Apply Multiple-Controlled Y rotation gate

Parameters

self (QuantumCircuit) – The QuantumCircuit object to apply the mcry gate on.
theta (float) – angle theta
q_controls (list(Qubit)) – The list of control qubits
q_target (Qubit) – The target qubit
q_ancillae (QuantumRegister or tuple(QuantumRegister, int)) – The list of ancillary qubits.
mode (string) – The implementation mode to use
use_basis_gates (bool) – use u1, u2, u3, cx, id

Raises

QiskitError – parameter errors

mcrz

ZZFeatureMap.mcrz(lam, q_controls, q_target, use_basis_gates=False)

Apply Multiple-Controlled Z rotation gate

Parameters

self (QuantumCircuit) – The QuantumCircuit object to apply the mcrz gate on.
lam (float) – angle lambda
q_controls (list(Qubit)) – The list of control qubits
q_target (Qubit) – The target qubit
use_basis_gates (bool) – use u1, u2, u3, cx, id

Raises

QiskitError – parameter errors

mct

ZZFeatureMap.mct(control_qubits, target_qubit, ancilla_qubits=None, mode='noancilla')

Apply MCXGate.

mcu1

ZZFeatureMap.mcu1(lam, control_qubits, target_qubit)

Apply MCU1Gate.

mcx

ZZFeatureMap.mcx(control_qubits, target_qubit, ancilla_qubits=None, mode='noancilla')

Apply MCXGate.

The multi-cX gate can be implemented using different techniques, which use different numbers of ancilla qubits and have varying circuit depth. These modes are: - ‘no-ancilla’: Requires 0 ancilla qubits. - ‘recursion’: Requires 1 ancilla qubit if more than 4 controls are used, otherwise 0. - ‘v-chain’: Requires 2 less ancillas than the number of control qubits. - ‘v-chain-dirty’: Same as for the clean ancillas (but the circuit will be longer).

measure

ZZFeatureMap.measure(qubit, cbit)

Measure quantum bit into classical bit (tuples).

Parameters

qubit (QuantumRegister|list|tuple) – quantum register
cbit (ClassicalRegister|list|tuple) – classical register

Returns

the attached measure instruction.

Return type

qiskit.Instruction

Raises

CircuitError – if qubit is not in this circuit or bad format; if cbit is not in this circuit or not creg.

measure_active

ZZFeatureMap.measure_active(inplace=True)

Adds measurement to all non-idle qubits. Creates a new ClassicalRegister with a size equal to the number of non-idle qubits being measured.

Returns a new circuit with measurements if inplace=False.

Parameters

inplace (bool) – All measurements inplace or return new circuit.

Returns

Returns circuit with measurements when inplace = False.

Return type

QuantumCircuit

measure_all

ZZFeatureMap.measure_all(inplace=True)

Adds measurement to all qubits. Creates a new ClassicalRegister with a size equal to the number of qubits being measured.

Returns a new circuit with measurements if inplace=False.

Parameters

inplace (bool) – All measurements inplace or return new circuit.

Returns

Returns circuit with measurements when inplace = False.

Return type

QuantumCircuit

mirror

ZZFeatureMap.mirror()

Mirror the circuit by reversing the instructions.

This is done by recursively mirroring all instructions. It does not invert any gate.

Returns

the mirrored circuit

Return type

QuantumCircuit

ms

ZZFeatureMap.ms(theta, qubits)

Apply MSGate.

num_connected_components

ZZFeatureMap.num_connected_components(unitary_only=False)

How many non-entangled subcircuits can the circuit be factored to.

Parameters

unitary_only (bool) – Compute only unitary part of graph.

Returns

Number of connected components in circuit.

Return type

int

num_nonlocal_gates

ZZFeatureMap.num_nonlocal_gates()

Return number of non-local gates (i.e. involving 2+ qubits).

Conditional nonlocal gates are also included.

num_tensor_factors

ZZFeatureMap.num_tensor_factors()

Computes the number of tensor factors in the unitary (quantum) part of the circuit only.

Notes

This is here for backwards compatibility, and will be removed in a future release of Qiskit. You should call num_unitary_factors instead.

num_unitary_factors

ZZFeatureMap.num_unitary_factors()

Computes the number of tensor factors in the unitary (quantum) part of the circuit only.

pauli_block

ZZFeatureMap.pauli_block(pauli_string)

Get the Pauli block for the feature map circuit.

pauli_evolution

ZZFeatureMap.pauli_evolution(pauli_string, time)

Get the evolution block for the given pauli string.

print_settings

ZZFeatureMap.print_settings()

Returns information about the setting.

Return type

str

Returns

The class name and the attributes/parameters of the instance as str.

qasm

ZZFeatureMap.qasm(formatted=False, filename=None)

Return OpenQASM string.

Parameters

formatted (bool) – Return formatted Qasm string.
filename (str) – Save Qasm to file with name ‘filename’.

Returns

If formatted=False.

Return type

str

Raises

ImportError – If pygments is not installed and formatted is True.

qbit_argument_conversion

ZZFeatureMap.qbit_argument_conversion(qubit_representation)

Converts several qubit representations (such as indexes, range, etc.) into a list of qubits.

Parameters

qubit_representation (Object) – representation to expand

Returns

Where each tuple is a qubit.

Return type

List(tuple)

r

ZZFeatureMap.r(theta, phi, qubit, *, q=None)

Apply RGate.

rcccx

ZZFeatureMap.rcccx(control_qubit1, control_qubit2, control_qubit3, target_qubit)

Apply RC3XGate.

rccx

ZZFeatureMap.rccx(control_qubit1, control_qubit2, target_qubit)

Apply RCCXGate.

remove_final_measurements

ZZFeatureMap.remove_final_measurements(inplace=True)

Removes final measurement on all qubits if they are present. Deletes the ClassicalRegister that was used to store the values from these measurements if it is idle.

Returns a new circuit without measurements if inplace=False.

Parameters

inplace (bool) – All measurements removed inplace or return new circuit.

Returns

Returns circuit with measurements removed when inplace = False.

Return type

QuantumCircuit

reset

ZZFeatureMap.reset(qubit)

Reset q.

rx

ZZFeatureMap.rx(theta, qubit, *, label=None, q=None)

Apply RXGate.

rxx

ZZFeatureMap.rxx(theta, qubit1, qubit2)

Apply RXXGate.

ry

ZZFeatureMap.ry(theta, qubit, *, label=None, q=None)

Apply RYGate.

ryy

ZZFeatureMap.ryy(theta, qubit1, qubit2)

Apply RYYGate.

rz

ZZFeatureMap.rz(phi, qubit, *, q=None)

Apply RZGate.

rzx

ZZFeatureMap.rzx(theta, qubit1, qubit2)

Apply RZXGate.

rzz

ZZFeatureMap.rzz(theta, qubit1, qubit2)

Apply RZZGate.

s

ZZFeatureMap.s(qubit, *, q=None)

Apply SGate.

sdg

ZZFeatureMap.sdg(qubit, *, q=None)

Apply SdgGate.

size

ZZFeatureMap.size()

Returns total number of gate operations in circuit.

Returns

Total number of gate operations.

Return type

int

snapshot

ZZFeatureMap.snapshot(label, snapshot_type='statevector', qubits=None, params=None)

Take a statevector snapshot of the internal simulator representation. Works on all qubits, and prevents reordering (like barrier). :param label: a snapshot label to report the result :type label: str :param snapshot_type: the type of the snapshot. :type snapshot_type: str :param qubits: the qubits to apply snapshot to [Default: None]. :type qubits: list or None :param params: the parameters for snapshot_type [Default: None]. :type params: list or None

Returns

with attached command

Return type

QuantumCircuit

Raises

ExtensionError – malformed command

snapshot_density_matrix

ZZFeatureMap.snapshot_density_matrix(label, qubits=None)

Take a density matrix snapshot of simulator state.

Parameters

label (str) – a snapshot label to report the result
qubits (list or None) – the qubits to apply snapshot to. If None all qubits will be snapshot [Default: None].

Returns

with attached instruction.

Return type

QuantumCircuit

Raises

ExtensionError – if snapshot is invalid.

snapshot_expectation_value

ZZFeatureMap.snapshot_expectation_value(label, op, qubits, single_shot=False, variance=False)

Take a snapshot of expectation value <O> of an Operator.

Parameters

label (str) – a snapshot label to report the result
op (Operator) – operator to snapshot
qubits (list) – the qubits to snapshot.
single_shot (bool) – return list for each shot rather than average [Default: False]
variance (bool) – compute variance of probabilities [Default: False]

Returns

with attached instruction.

Return type

QuantumCircuit

Raises

ExtensionError – if snapshot is invalid.

snapshot_probabilities

ZZFeatureMap.snapshot_probabilities(label, qubits, variance=False)

Take a probability snapshot of the simulator state.

Parameters

label (str) – a snapshot label to report the result
qubits (list) – the qubits to snapshot.
variance (bool) – compute variance of probabilities [Default: False]

Returns

with attached instruction.

Return type

QuantumCircuit

Raises

ExtensionError – if snapshot is invalid.

snapshot_stabilizer

ZZFeatureMap.snapshot_stabilizer(label)

Take a stabilizer snapshot of the simulator state.

Parameters

label (str) – a snapshot label to report the result.

Returns

with attached instruction.

Return type

QuantumCircuit

Raises

ExtensionError – if snapshot is invalid.

Additional Information:

This snapshot is always performed on all qubits in a circuit. The number of qubits parameter specifies the size of the instruction as a barrier and should be set to the number of qubits in the circuit.

snapshot_statevector

ZZFeatureMap.snapshot_statevector(label)

Take a statevector snapshot of the simulator state.

Parameters

label (str) – a snapshot label to report the result.

Returns

with attached instruction.

Return type

QuantumCircuit

Raises

ExtensionError – if snapshot is invalid.

Additional Information:

squ

ZZFeatureMap.squ(unitary_matrix, qubit, mode='ZYZ', up_to_diagonal=False, *, u=None)

Decompose an arbitrary 2*2 unitary into three rotation gates.

Note that the decomposition is up to a global phase shift. (This is a well known decomposition, which can be found for example in Nielsen and Chuang’s book “Quantum computation and quantum information”.)

Parameters

unitary_matrix (ndarray) – 2*2 unitary (given as a (complex) ndarray).
qubit (QuantumRegister |Qubit) – The qubit which the gate is acting on.
mode (string) – determines the used decomposition by providing the rotation axes. The allowed modes are: “ZYZ” (default)
up_to_diagonal (bool) – if set to True, the single-qubit unitary is decomposed up to a diagonal matrix, i.e. a unitary u’ is implemented such that there exists a 2*2 diagonal gate d with u = d.dot(u’)
u (ndarray) – Deprecated, use unitary_matrix instead.

Returns

The single-qubit unitary instruction attached to the circuit.

Return type

InstructionSet

Raises

QiskitError – if the format is wrong; if the array u is not unitary

swap

ZZFeatureMap.swap(qubit1, qubit2)

Apply SwapGate.

t

ZZFeatureMap.t(qubit, *, q=None)

Apply TGate.

tdg

ZZFeatureMap.tdg(qubit, *, q=None)

Apply TdgGate.

to_gate

ZZFeatureMap.to_gate(parameter_map=None)

Create a Gate out of this circuit.

Parameters

parameter_map (dict) – For parameterized circuits, a mapping from parameters in the circuit to parameters to be used in the gate. If None, existing circuit parameters will also parameterize the gate.

Returns

a composite gate encapsulating this circuit (can be decomposed back)

Return type

Gate

to_instruction

ZZFeatureMap.to_instruction(parameter_map=None)

Create an Instruction out of this circuit.

Parameters

parameter_map (dict) – For parameterized circuits, a mapping from parameters in the circuit to parameters to be used in the instruction. If None, existing circuit parameters will also parameterize the instruction.

Returns

a composite instruction encapsulating this circuit (can be decomposed back)

Return type

qiskit.circuit.Instruction

toffoli

ZZFeatureMap.toffoli(control_qubit1, control_qubit2, target_qubit, *, ctl1=None, ctl2=None, tgt=None)

Apply CCXGate.

u1

ZZFeatureMap.u1(theta, qubit, *, q=None)

Apply U1Gate.

u2

ZZFeatureMap.u2(phi, lam, qubit, *, q=None)

Apply U2Gate.

u3

ZZFeatureMap.u3(theta, phi, lam, qubit, *, q=None)

Apply U3Gate.

uc

ZZFeatureMap.uc(gate_list, q_controls, q_target, up_to_diagonal=False)

Attach a uniformly controlled gates (also called multiplexed gates) to a circuit.

The decomposition was introduced by Bergholm et al. in https://arxiv.org/pdf/quant-ph/0410066.pdf.

Parameters

gate_list (list[ndarray]) – list of two qubit unitaries [U_0,…,U_{2^k-1}], where each single-qubit unitary U_i is a given as a 2*2 array
q_controls (QuantumRegister|list[(QuantumRegister,int)]) – list of k control qubits. The qubits are ordered according to their significance in the computational basis. For example if q_controls=[q[1],q[2]] (with q = QuantumRegister(2)), the unitary U_0 is performed if q[1] and q[2] are in the state zero, U_1 is performed if q[2] is in the state zero and q[1] is in the state one, and so on
q_target (QuantumRegister|(QuantumRegister,int)) – target qubit, where we act on with the single-qubit gates.
up_to_diagonal (bool) – If set to True, the uniformly controlled gate is decomposed up to a diagonal gate, i.e. a unitary u’ is implemented such that there exists a diagonal gate d with u = d.dot(u’), where the unitary u describes the uniformly controlled gate

Returns

the uniformly controlled gate is attached to the circuit.

Return type

QuantumCircuit

Raises

QiskitError – if the list number of control qubits does not correspond to the provided number of single-qubit unitaries; if an input is of the wrong type

ucg

ZZFeatureMap.ucg(angle_list, q_controls, q_target, up_to_diagonal=False)

Deprecated version of uc.

ucrx

ZZFeatureMap.ucrx(angle_list, q_controls, q_target)

Attach a uniformly controlled (also called multiplexed) Rx rotation gate to a circuit.

The decomposition is base on https://arxiv.org/pdf/quant-ph/0406176.pdf by Shende et al.

Parameters

angle_list (list) – list of (real) rotation angles $[a_0,...,a_{2^k-1}]$
q_controls (QuantumRegister|list) – list of k control qubits (or empty list if no controls). The control qubits are ordered according to their significance in increasing order: For example if q_controls=[q[0],q[1]] (with q = QuantumRegister(2)), the rotation Rx(a_0) is performed if q[0] and q[1] are in the state zero, the rotation Rx(a_1) is performed if q[0] is in the state one and q[1] is in the state zero, and so on
q_target (QuantumRegister|Qubit) – target qubit, where we act on with the single-qubit rotation gates

Returns

the uniformly controlled rotation gate is attached to the circuit.

Return type

QuantumCircuit

Raises

QiskitError – if the list number of control qubits does not correspond to the provided number of single-qubit unitaries; if an input is of the wrong type

ucry

ZZFeatureMap.ucry(angle_list, q_controls, q_target)

Attach a uniformly controlled (also called multiplexed) Ry rotation gate to a circuit.

The decomposition is base on https://arxiv.org/pdf/quant-ph/0406176.pdf by Shende et al.

Parameters

angle_list (list[numbers) – list of (real) rotation angles $[a_0,...,a_{2^k-1}]$
q_controls (QuantumRegister|list[Qubit]) – list of k control qubits (or empty list if no controls). The control qubits are ordered according to their significance in increasing order: For example if q_controls=[q[0],q[1]] (with q = QuantumRegister(2)), the rotation Ry(a_0) is performed if q[0] and q[1] are in the state zero, the rotation Ry(a_1) is performed if q[0] is in the state one and q[1] is in the state zero, and so on
q_target (QuantumRegister|Qubit) – target qubit, where we act on with the single-qubit rotation gates

Returns

the uniformly controlled rotation gate is attached to the circuit.

Return type

QuantumCircuit

Raises

QiskitError – if the list number of control qubits does not correspond to the provided number of single-qubit unitaries; if an input is of the wrong type

ucrz

ZZFeatureMap.ucrz(angle_list, q_controls, q_target)

Attach a uniformly controlled (also called multiplexed gates) Rz rotation gate to a circuit.

The decomposition is base on https://arxiv.org/pdf/quant-ph/0406176.pdf by Shende et al.

Parameters

angle_list (list[numbers) – list of (real) rotation angles [a_0,…,a_{2^k-1}]
q_controls (QuantumRegister|list[Qubit]) – list of k control qubits (or empty list if no controls). The control qubits are ordered according to their significance in increasing order: For example if q_controls=[q[1],q[2]] (with q = QuantumRegister(2)), the rotation Rz(a_0)is performed if q[1] and q[2] are in the state zero, the rotation Rz(a_1) is performed if q[1] is in the state one and q[2] is in the state zero, and so on
q_target (QuantumRegister|Qubit) – target qubit, where we act on with the single-qubit rotation gates

Returns

the uniformly controlled rotation gate is attached to the circuit.

Return type

QuantumCircuit

Raises

QiskitError – if the list number of control qubits does not correspond to the provided number of single-qubit unitaries; if an input is of the wrong type

ucx

ZZFeatureMap.ucx(angle_list, q_controls, q_target)

Deprecated version of ucrx.

ucy

ZZFeatureMap.ucy(angle_list, q_controls, q_target)

Deprecated version of ucry.

ucz

ZZFeatureMap.ucz(angle_list, q_controls, q_target)

Deprecated version of ucrz.

unitary

ZZFeatureMap.unitary(obj, qubits, label=None)

Apply unitary gate to q.

width

ZZFeatureMap.width()

Return number of qubits plus clbits in circuit.

Returns

Width of circuit.

Return type

int

x

ZZFeatureMap.x(qubit, *, label=None, ctrl_state=None, q=None)

Apply XGate.

y

ZZFeatureMap.y(qubit, *, q=None)

Apply YGate.

z

ZZFeatureMap.z(qubit, *, q=None)

Apply ZGate.

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