QuantumCircuit
class
class qiskit.circuit.QuantumCircuit(*regs, name=None, global_phase=0, metadata=None, inputs=(), captures=(), declarations=())
Core Qiskit representation of a quantum circuit.
For more details setting the QuantumCircuit
in context of all of the data structures that go with it, how it fits into the rest of the qiskit
package, and the different regimes of quantumcircuit descriptions in Qiskit, see the modulelevel documentation of qiskit.circuit
.
Circuit attributes
QuantumCircuit
has a small number of public attributes, which are mostly older functionality. Most of its functionality is accessed through methods.
A small handful of the attributes are intentionally mutable, the rest are data attributes that should be considered immutable.
Mutable attribute  Summary 

global_phase  The global phase of the circuit, measured in radians. 
metadata  Arbitrary user mapping, which Qiskit will preserve through the transpiler, but otherwise completely ignore. 
name  An optional string name for the circuit. 
Immutable data attribute  Summary 

ancillas  List of AncillaQubit s tracked by the circuit. 
calibrations  Custom usersupplied pulse calibrations for individual instructions. 
cregs  List of ClassicalRegister s tracked by the circuit. 
clbits  List of Clbit s tracked by the circuit. 
data  List of individual CircuitInstruction s that make up the circuit. 
duration  Total duration of the circuit, added by scheduling transpiler passes. 
layout  Hardware layout and routing information added by the transpiler. 
num_ancillas  The number of ancilla qubits in the circuit. 
num_clbits  The number of clbits in the circuit. 
num_captured_vars  Number of captured realtime classical variables. 
num_declared_vars  Number of locally declared realtime classical variables in the outer circuit scope. 
num_input_vars  Number of input realtime classical variables. 
num_parameters  Number of compiletime Parameter s in the circuit. 
num_qubits  Number of qubits in the circuit. 
num_vars  Total number of realtime classical variables in the outer circuit scope. 
op_start_times  Start times of scheduled operations, added by scheduling transpiler passes. 
parameters  Ordered setlike view of the compiletime Parameter s tracked by the circuit. 
qregs  List of QuantumRegister s tracked by the circuit. 
qubits  List of Qubit s tracked by the circuit. 
unit  The unit of the duration field. 
The core attribute is data
. This is a sequencelike object that exposes the CircuitInstruction
s contained in an ordered form. You generally should not mutate this object directly; QuantumCircuit
is only designed for appendonly operations (which should use append()
). Most operations that mutate circuits in place should be written as transpiler passes (qiskit.transpiler
).
data
The circuit data (instructions and context).
Returns
a listlike object containing the CircuitInstruction
s for each instruction.
Return type
QuantumCircuitData
Alongside the data
, the global_phase
of a circuit can have some impact on its output, if the circuit is used to describe a Gate
that may be controlled. This is measured in radians and is directly settable.
global_phase
The global phase of the current circuit scope in radians.
The name
of a circuit becomes the name of the Instruction
or Gate
resulting from to_instruction()
and to_gate()
calls, which can be handy for visualizations.
name
Type: str
A humanreadable name for the circuit.
You can attach arbitrary metadata
to a circuit. No part of core Qiskit will inspect this or change its behavior based on metadata, but it will be faithfully passed through the transpiler, so you can tag your circuits yourself. When serializing a circuit with QPY (see qiskit.qpy
), the metadata will be JSONserialized and you may need to pass a custom serializer to handle nonJSONcompatible objects within it (see qpy.dump()
for more detail). This field is ignored during export to OpenQASM 2 or 3.
metadata
Arbitrary userdefined 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.
QuantumCircuit
exposes data attributes tracking its internal quantum and classical bits and registers. These appear as Python list
s, but you should treat them as immutable; changing them will at best have no effect, and more likely will simply corrupt the internal data of the QuantumCircuit
.
qregs
Type: list[QuantumRegister]
A list of the QuantumRegister
s in this circuit. You should not mutate this.
cregs
Type: list[ClassicalRegister]
A list of the ClassicalRegister
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.
ancillas
A list of AncillaQubit
s in the order that they were added. You should not mutate this.
clbits
A list of Clbit
s in the order that they were added. You should not mutate this.
The compiletime parameters present in instructions on the circuit are available in parameters
. This has a canonical order (mostly lexical, except in the case of ParameterVector
), which matches the order that parameters will be assigned when using the list forms of assign_parameters()
, but also supports set
like constanttime membership testing.
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.
The storage of any manual pulselevel calibrations for individual instructions on the circuit is in calibrations
. This presents as a dict
, but should not be mutated directly; use the methods discussed in Manual calibration of instructions.
calibrations
Return calibration dictionary.
The custom pulse definition of a given gate is of the form {'gate_name': {(qubits, params): schedule}}
If you have transpiled your circuit, so you have a physical circuit, you can inspect the layout
attribute for information stored by the transpiler about how the virtual qubits of the source circuit map to the hardware qubits of your physical circuit, both at the start and end of the circuit.
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.
If your circuit was also scheduled as part of a transpilation, it will expose the individual timings of each instruction, along with the total duration
of the circuit.
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.
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.
Finally, QuantumCircuit
exposes several simple properties as dynamic readonly numeric attributes.
num_ancillas
Return the number of ancilla qubits.
num_clbits
Return number of classical bits.
num_captured_vars
The number of realtime 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 nonzero, num_input_vars
must be zero.
num_declared_vars
The number of realtime 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 realtime classical variables in the circuit marked as circuit inputs.
This is the length of the iter_input_vars()
iterable. If this is nonzero, num_captured_vars
must be zero.
num_parameters
The number of parameter objects in the circuit.
num_qubits
Return number of qubits.
num_vars
The number of realtime classical variables in the circuit.
This is the length of the iter_vars()
iterable.
Creating new circuits
Method  Summary 

__init__()  Default constructor of noinstruction circuits. 
copy()  Make a complete copy of an existing circuit. 
copy_empty_like()  Copy data objects from one circuit into a new one without any instructions. 
from_instructions()  Infer data objects needed from a list of instructions. 
from_qasm_file()  Legacy interface to qasm2.load() . 
from_qasm_str()  Legacy interface to qasm2.loads() . 
The default constructor (QuantumCircuit(...)
) produces a circuit with no initial instructions. The arguments to the default constructor can be used to seed the circuit with quantum and classical data storage, and to provide a name, global phase and arbitrary metadata. All of these fields can be expanded later.
__init__
__init__(*regs, name=None, global_phase=0, metadata=None, inputs=(), captures=(), declarations=())
Default constructor of QuantumCircuit
.
Parameters

regs (Register int  Sequence[Bit]) –
The registers to be included in the circuit.

If a list of
Register
objects, represents theQuantumRegister
and/orClassicalRegister
objects to include in the circuit.For example:
QuantumCircuit(QuantumRegister(4))
QuantumCircuit(QuantumRegister(4), ClassicalRegister(3))
QuantumCircuit(QuantumRegister(4, 'qr0'), QuantumRegister(2, 'qr1'))

If a list of
int
, the amount of qubits and/or classical bits to include in the circuit. It can either be a single int for just the number of quantum bits, or 2 ints for the number of quantum bits and classical bits, respectively.For example:
QuantumCircuit(4) # A QuantumCircuit with 4 qubits
QuantumCircuit(4, 3) # A QuantumCircuit with 4 qubits and 3 classical bits

If a list of python lists containing
Bit
objects, a collection ofBit
s to be added to the circuit.


name (str  None) – the name of the quantum circuit. If not set, an automatically generated string will be assigned.

global_phase (ParameterValueType) – The global phase of the circuit in radians.

metadata (dict  None) – Arbitrary key value metadata to associate with the circuit. This gets stored as freeform data in a dict in the
metadata
attribute. It will not be directly used in the circuit. 
inputs (Iterable[expr.Var]) – any variables to declare as
input
runtime variables for this circuit. These should already be existingexpr.Var
nodes that you build from somewhere else; if you need to create the inputs as well, useQuantumCircuit.add_input()
. The variables given in this argument will be passed directly toadd_input()
. A circuit cannot have bothinputs
andcaptures
. 
captures (Iterable[expr.Var]) – any variables that that this circuit scope should capture from a containing scope. The variables given here will be passed directly to
add_capture()
. A circuit cannot have bothinputs
andcaptures
. 
declarations (Mapping[expr.Var, expr.Expr]  Iterable[Tuple[expr.Var, expr.Expr]]) –
any variables that this circuit should declare and initialize immediately. You can order this input so that later declarations depend on earlier ones (including inputs or captures). If you need to depend on values that will be computed later at runtime, use
add_var()
at an appropriate point in the circuit execution.This argument is intended for convenient circuit initialization when you already have a set of created variables. The variables used here will be directly passed to
add_var()
, which you can use directly if this is the first time you are creating the variable.
Raises
 CircuitError – if the circuit name, if given, is not valid.
 CircuitError – if both
inputs
andcaptures
are given.
If you have an existing circuit, you can produce a copy of it using copy()
, including all its instructions. This is useful if you want to keep partial circuits while extending another, or to have a version you can mutate inplace while leaving the prior one intact.
copy
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
Similarly, if you want a circuit that contains all the same data objects (bits, registers, variables, etc) but with none of the instructions, you can use copy_empty_like()
. This is quite common when you want to build up a new layer of a circuit to then use apply onto the back with compose()
, or to do a full rewrite of a circuit’s instructions.
copy_empty_like
copy_empty_like(name=None, *, vars_mode='alike')
Return a copy of self with the same structure but empty.
That structure includes:
 name, calibrations and other metadata
 global phase
 all the qubits and clbits, including the registers
 the realtime variables defined in the circuit, handled according to the
vars
keyword argument.
If the circuit contains any local variable declarations (those added by the declarations
argument to the circuit constructor, or using add_var()
), they may be uninitialized in the output circuit. You will need to manually add store instructions for them (see Store
and QuantumCircuit.store()
) to initialize them.
Parameters

name (str  None) – Name for the copied circuit. If None, then the name stays the same.

vars_mode (Literal['alike', 'captures', 'drop']) –
The mode to handle realtime variables in.
alike
The variables in the output circuit will have the same declaration semantics as in the original circuit. For example,
input
variables in the source will beinput
variables in the output circuit.captures
All variables will be converted to captured variables. This is useful when you are building a new layer for an existing circuit that you will want to
compose()
onto the base, sincecompose()
can inline captures onto the base circuit (but not other variables).drop
The output circuit will have no variables defined.
Returns
An empty copy of self.
Return type
In some cases, it is most convenient to generate a list of CircuitInstruction
s separately to an entire circuit context, and then to build a circuit from this. The from_instructions()
constructor will automatically capture all Qubit
and Clbit
instances used in the instructions, and create a new QuantumCircuit
object that has the correct resources and all the instructions.
from_instructions
static from_instructions(instructions, *, qubits=(), clbits=(), name=None, global_phase=0, metadata=None)
Construct a circuit from an iterable of CircuitInstruction
s.
Parameters
 instructions (Iterable[CircuitInstruction tuple[qiskit.circuit.Instruction]  tuple[qiskit.circuit.Instruction, Iterable[Qubit]]  tuple[qiskit.circuit.Instruction, Iterable[Qubit], Iterable[Clbit]]]) – The instructions to add to the circuit.
 qubits (Iterable[Qubit]) – Any qubits to add to the circuit. This argument can be used, for example, to enforce a particular ordering of qubits.
 clbits (Iterable[Clbit]) – Any classical bits to add to the circuit. This argument can be used, for example, to enforce a particular ordering of classical bits.
 name (str  None) – The name of the circuit.
 global_phase (ParameterValueType) – The global phase of the circuit in radians.
 metadata (dict  None) – Arbitrary key value metadata to associate with the circuit.
Returns
The quantum circuit.
Return type
QuantumCircuit
also still has two constructor methods that are legacy wrappers around the importers in qiskit.qasm2
. These automatically apply the legacy compatibility settings of load()
and loads()
.
from_qasm_file
static from_qasm_file(path)
Read an OpenQASM 2.0 program from a file and convert to an instance of QuantumCircuit
.
Parameters
path (str) – Path to the file for an OpenQASM 2 program
Returns
The QuantumCircuit object for the input OpenQASM 2.
Return type
qasm2.load()
: the complete interface to the OpenQASM 2 importer.
from_qasm_str
static from_qasm_str(qasm_str)
Convert a string containing an OpenQASM 2.0 program to a QuantumCircuit
.
Parameters
qasm_str (str) – A string containing an OpenQASM 2.0 program.
Returns
The QuantumCircuit object for the input OpenQASM 2
Return type
qasm2.loads()
: the complete interface to the OpenQASM 2 importer.
Data objects on circuits
Adding data objects
Method  Adds this kind of data 

add_bits()  Qubit s and Clbit s. 
add_register()  QuantumRegister and ClassicalRegister . 
add_var()  Var nodes with local scope and initializers. 
add_input()  Var nodes that are treated as circuit inputs. 
add_capture()  Var nodes captured from containing scopes. 
add_uninitialized_var()  Var nodes with local scope and undefined state. 
Typically you add most of the data objects (Qubit
, Clbit
, ClassicalRegister
, etc) to the circuit as part of using the __init__()
default constructor, or copy_empty_like()
. However, it is also possible to add these afterwards. Typed classical data, such as standalone Var
nodes (see Realtime classical computation), can be both constructed and added with separate methods.
New registerless Qubit
and Clbit
objects are added using add_bits()
. These objects must not already be present in the circuit. You can check if a bit exists in the circuit already using find_bit()
.
add_bits
Registers are added to the circuit with add_register()
. In this method, it is not an error if some of the bits are already present in the circuit. In this case, the register will be an “alias” over the bits. This is not generally wellsupported by hardware backends; it is probably best to stay away from relying on it. The registers a given bit is in are part of the return of find_bit()
.
add_register
Realtime, typed classical data is represented on the circuit by Var
nodes with a welldefined Type
. It is possible to instantiate these separately to a circuit (see Var.new()
), but it is often more convenient to use circuit methods that will automatically manage the types and expression initialization for you. The two most common methods are add_var()
(locally scoped variables) and add_input()
(inputs to the circuit).
add_var
add_var(name_or_var, /, initial)
Add a classical variable with automatic storage and scope to this circuit.
The variable is considered to have been “declared” at the beginning of the circuit, but it only becomes initialized at the point of the circuit that you call this method, so it can depend on variables defined before it.
Parameters

name_or_var (str expr.Var) – either a string of the variable name, or an existing instance of
Var
to reuse. Variables cannot shadow names that are already in use within the circuit. 
initial (Any) –
the value to initialize this variable with. If the first argument was given as a string name, the type of the resulting variable is inferred from the initial expression; to control this more manually, either use
Var.new()
to manually construct a new variable with the desired type, or useexpr.cast()
to cast the initializer to the desired type.This must be either a
Expr
node, or a value that can be lifted to one usingexpr.lift
.
Returns
The created variable. If a Var
instance was given, the exact same object will be returned.
Raises
CircuitError – if the variable cannot be created due to shadowing an existing variable.
Return type
Examples
Define a new variable given just a name and an initializer expression:
from qiskit.circuit import QuantumCircuit
qc = QuantumCircuit(2)
my_var = qc.add_var("my_var", False)
Reuse a variable that may have been taken from a related circuit, or otherwise constructed manually, and initialize it to some more complicated expression:
from qiskit.circuit import QuantumCircuit, QuantumRegister, ClassicalRegister
from qiskit.circuit.classical import expr, types
my_var = expr.Var.new("my_var", types.Uint(8))
cr1 = ClassicalRegister(8, "cr1")
cr2 = ClassicalRegister(8, "cr2")
qc = QuantumCircuit(QuantumRegister(8), cr1, cr2)
# Get some measurement results into each register.
qc.h(0)
for i in range(1, 8):
qc.cx(0, i)
qc.measure(range(8), cr1)
qc.reset(range(8))
qc.h(0)
for i in range(1, 8):
qc.cx(0, i)
qc.measure(range(8), cr2)
# Now when we add the variable, it is initialized using the realtime state of the
# two classical registers we measured into above.
qc.add_var(my_var, expr.bit_and(cr1, cr2))
add_input
add_input(name_or_var: str, type_: Type, /) → Var
add_input(name_or_var: Var, type_: None = None, /) → Var
Register a variable as an input to the circuit.
Parameters
 name_or_var – either a string name, or an existing
Var
node to use as the input variable.  type – if the name is given as a string, then this must be a
Type
to use for the variable. If the variable is given as an existingVar
, then this must not be given, and will instead be read from the object itself.
Returns
the variable created, or the same variable as was passed in.
Raises
CircuitError – if the variable cannot be created due to shadowing an existing variable.
In addition, there are two lowerlevel methods that can be useful for programmatic generation of circuits. When working interactively, you will most likely not need these; most uses of add_uninitialized_var()
are part of copy_empty_like()
, and most uses of add_capture()
would be better off using the controlflow builder interface.
add_uninitialized_var
add_uninitialized_var(var, /)
Add a variable with no initializer.
In most cases, you should use add_var()
to initialize the variable. To use this function, you must already hold a Var
instance, as the use of the function typically only makes sense in copying contexts.
Qiskit makes no assertions about what an uninitialized variable will evaluate to at runtime, and some hardware may reject this as an error.
You should treat this function with caution, and as a lowlevel primitive that is useful only in special cases of programmatically rebuilding two like circuits.
Parameters
var (Var) – the variable to add.
add_capture
add_capture(var)
Add a variable to the circuit that it should capture from a scope it will be contained within.
This method requires a Var
node to enforce that you’ve got a handle to one, because you will need to declare the same variable using the same object into the outer circuit.
This is a lowlevel method, which is only really useful if you are manually constructing controlflow operations. You typically will not need to call this method, assuming you are using the builder interface for controlflow scopes (with
contextmanager statements for if_test()
and the other scoping constructs). The builder interface will automatically make the inner scopes closures on your behalf by capturing any variables that are used within them.
Parameters
var (Var) – the variable to capture from an enclosing scope.
Raises
CircuitError – if the variable cannot be created due to shadowing an existing variable.
Working with bits and registers
A Bit
instance is, on its own, just a unique handle for circuits to use in their own contexts. If you have got a Bit
instance and a circuit, just can find the contexts that the bit exists in using find_bit()
, such as its integer index in the circuit and any registers it is contained in.
find_bit
find_bit(bit)
Find locations in the circuit which can be used to reference a given Bit
.
In particular, this function can find the integer index of a qubit, which corresponds to its hardware index for a transpiled circuit.
The circuit index of a AncillaQubit
will be its index in qubits
, not ancillas
.
Parameters
bit (Bit) – The bit to locate.
Returns
A 2tuple. The first element (index
) contains the index at which the Bit
can be found (in either qubits
, clbits
, depending on its type). The second element (registers
) is a list of (register, index)
pairs with an entry for each Register
in the circuit which contains the Bit
(and the index in the Register
at which it can be found).
Return type
namedtuple(int, List[Tuple(Register, int)])
Raises
 CircuitError – If the supplied
Bit
was of an unknown type.  CircuitError – If the supplied
Bit
could not be found on the circuit.
Examples
Loop through a circuit, getting the qubit and clbit indices of each operation:
from qiskit.circuit import QuantumCircuit, Qubit
qc = QuantumCircuit(3, 3)
qc.h(0)
qc.cx(0, 1)
qc.cx(1, 2)
qc.measure([0, 1, 2], [0, 1, 2])
# The `.qubits` and `.clbits` fields are not integers.
assert isinstance(qc.data[0].qubits[0], Qubit)
# ... but we can use `find_bit` to retrieve them.
assert qc.find_bit(qc.data[0].qubits[0]).index == 0
simple = [
(
instruction.operation.name,
[qc.find_bit(bit).index for bit in instruction.qubits],
[qc.find_bit(bit).index for bit in instruction.clbits],
)
for instruction in qc.data
]
Similarly, you can query a circuit to see if a register has already been added to it by using has_register()
.
has_register
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
Working with compiletime parameters
A more complete discussion of what compiletime parametrization is, and how it fits into Qiskit’s data model.
Unlike bits, registers, and realtime typed classical data, compiletime symbolic parameters are not manually added to a circuit. Their presence is inferred by being contained in operations added to circuits and the global phase. An ordered list of all parameters currently in a circuit is at QuantumCircuit.parameters
.
The most common operation on Parameter
instances is to replace them in symbolic operations with some numeric value, or another symbolic expression. This is done with assign_parameters()
.
assign_parameters
assign_parameters(parameters: Mapping[Parameter, ParameterExpression  float]  Iterable[ParameterExpression  float], inplace: Literal[False] = False, *, flat_input: bool = False, strict: bool = True) → QuantumCircuit
assign_parameters(parameters: Mapping[Parameter, ParameterExpression  float]  Iterable[ParameterExpression  float], inplace: Literal[True] = False, *, flat_input: bool = False, strict: bool = True) → None
Assign parameters to new parameters or values.
If parameters
is passed as a dictionary, the keys should be Parameter
instances in the current circuit. The values of the dictionary can either be numeric values or new parameter objects.
If parameters
is passed as a list or array, the elements are assigned to the current parameters in the order of parameters
which is sorted alphabetically (while respecting the ordering in ParameterVector
objects).
The values can be assigned to the current circuit object or to a copy of it.
When parameters
is given as a mapping, it is permissible to have keys that are strings of the parameter names; these will be looked up using get_parameter()
. You can also have keys that are ParameterVector
instances, and in this case, the dictionary value should be a sequence of values of the same length as the vector.
If you use either of these cases, you must leave the setting flat_input=False
; changing this to True
enables the fast path, where all keys must be Parameter
instances.
Parameters
 parameters – Either a dictionary or iterable specifying the new parameter values.
 inplace – If False, a copy of the circuit with the bound parameters is returned. If True the circuit instance itself is modified.
 flat_input – If
True
andparameters
is a mapping type, it is assumed to be exactly a mapping of{parameter: value}
. By default (False
), the mapping may also containParameterVector
keys that point to a corresponding sequence of values, and these will be unrolled during the mapping, or string keys, which will be converted toParameter
instances usingget_parameter()
.  strict – If
False
, any parameters given in the mapping that are not used in the circuit will be ignored. IfTrue
(the default), an error will be raised indicating a logic error.
Raises
 CircuitError – If parameters is a dict and contains parameters not present in the circuit.
 ValueError – If parameters is a list/array and the length mismatches the number of free parameters in the circuit.
Returns
A copy of the circuit with bound parameters if inplace
is False, otherwise None.
Examples
Create a parameterized circuit and assign the parameters inplace.
from qiskit.circuit import QuantumCircuit, Parameter
circuit = QuantumCircuit(2)
params = [Parameter('A'), Parameter('B'), Parameter('C')]
circuit.ry(params[0], 0)
circuit.crx(params[1], 0, 1)
circuit.draw('mpl')
circuit.assign_parameters({params[0]: params[2]}, inplace=True)
circuit.draw('mpl')
Bind the values outofplace by list and get a copy of the original circuit.
from qiskit.circuit import QuantumCircuit, ParameterVector
circuit = QuantumCircuit(2)
params = ParameterVector('P', 2)
circuit.ry(params[0], 0)
circuit.crx(params[1], 0, 1)
bound_circuit = circuit.assign_parameters([1, 2])
bound_circuit.draw('mpl')
circuit.draw('mpl')
The circuit tracks parameters by Parameter
instances themselves, and forbids having multiple parameters of the same name to avoid some problems when interoperating with OpenQASM or other external formats. You can use has_parameter()
and get_parameter()
to query the circuit for a parameter with the given string name.
has_parameter
has_parameter(name_or_param, /)
Check whether a parameter object exists in this circuit.
Parameters
name_or_param (str Parameter) – the parameter, or name of a parameter to check. If this is a Parameter
node, the parameter must be exactly the given one for this function to return True
.
Returns
whether a matching parameter is assignable in this circuit.
Return type
QuantumCircuit.get_parameter()
Retrieve the Parameter
instance from this circuit by name.
A similar method to this, but for runtime expr.Var
variables instead of compiletime Parameter
s.
get_parameter
get_parameter(name: str, default: T) → Parameter  T
get_parameter(name: str, default: ellipsis = Ellipsis) → Parameter
Retrieve a compiletime parameter that is accessible in this circuit scope by name.
Parameters
 name – the name of the parameter to retrieve.
 default – if given, this value will be returned if the parameter is not present. If it is not given, a
KeyError
is raised instead.
Returns
The corresponding parameter.
Raises
KeyError – if no default is given, but the parameter does not exist in the circuit.
Examples
Retrieve a parameter by name from a circuit:
from qiskit.circuit import QuantumCircuit, Parameter
my_param = Parameter("my_param")
# Create a parametrized circuit.
qc = QuantumCircuit(1)
qc.rx(my_param, 0)
# We can use 'my_param' as a parameter, but let's say we've lost the Python object
# and need to retrieve it.
my_param_again = qc.get_parameter("my_param")
assert my_param is my_param_again
Get a variable from a circuit by name, returning some default if it is not present:
assert qc.get_parameter("my_param", None) is my_param
assert qc.get_parameter("unknown_param", None) is None
Working with realtime typed classical data
Modulelevel documentation for how the variable, expression and typesystems work, the objects used to represent them, and the classical operations available.
Realtime classical computation
A discussion of how realtime data fits into the entire qiskit.circuit
data model as a whole.
The methods for adding new Var
variables to a circuit after initialization.
You can retrive a Var
instance attached to a circuit by using its variable name using get_var()
, or check if a circuit contains a given variable with has_var()
.
get_var
get_var(name: str, default: T) → Var  T
get_var(name: str, default: ellipsis = Ellipsis) → Var
Retrieve a variable that is accessible in this circuit scope by name.
Parameters
 name – the name of the variable to retrieve.
 default – if given, this value will be returned if the variable is not present. If it is not given, a
KeyError
is raised instead.
Returns
The corresponding variable.
Raises
KeyError – if no default is given, but the variable does not exist.
Examples
Retrieve a variable by name from a circuit:
from qiskit.circuit import QuantumCircuit
# Create a circuit and create a variable in it.
qc = QuantumCircuit()
my_var = qc.add_var("my_var", False)
# We can use 'my_var' as a variable, but let's say we've lost the Python object and
# need to retrieve it.
my_var_again = qc.get_var("my_var")
assert my_var is my_var_again
Get a variable from a circuit by name, returning some default if it is not present:
assert qc.get_var("my_var", None) is my_var
assert qc.get_var("unknown_variable", None) is None
has_var
has_var(name_or_var, /)
Check whether a variable is accessible in this scope.
Parameters
name_or_var (str expr.Var) – the variable, or name of a variable to check. If this is a expr.Var
node, the variable must be exactly the given one for this function to return True
.
Returns
whether a matching variable is accessible.
Return type
Retrieve the expr.Var
instance from this circuit by name.
QuantumCircuit.has_parameter()
A similar method to this, but for compiletime Parameter
s instead of runtime expr.Var
variables.
There are also several iterator methods that you can use to get the full set of variables tracked by a circuit. At least one of iter_input_vars()
and iter_captured_vars()
will be empty, as inputs and captures are mutually exclusive. All of the iterators have corresponding dynamic properties on QuantumCircuit
that contain their length: num_vars
, num_input_vars
, num_captured_vars
and num_declared_vars
.
iter_vars
iter_vars()
Get an iterable over all realtime classical variables in scope within this circuit.
This method will iterate over all variables in scope. For more finegrained iterators, see iter_declared_vars()
, iter_input_vars()
and iter_captured_vars()
.
Return type
iter_input_vars
iter_input_vars()
Get an iterable over all realtime classical variables that are declared as inputs to this circuit scope. This excludes locally declared variables (see iter_declared_vars()
) and captured variables (see iter_captured_vars()
).
Return type
iter_captured_vars
iter_captured_vars()
Get an iterable over all realtime classical variables that are captured by this circuit scope from a containing scope. This excludes input variables (see iter_input_vars()
) and locally declared variables (see iter_declared_vars()
).
Return type
iter_declared_vars
iter_declared_vars()
Get an iterable over all realtime classical variables that are declared with automatic storage duration in this scope. This excludes input variables (see iter_input_vars()
) and captured variables (see iter_captured_vars()
).
Return type
Adding operations to circuits
You can add anything that implements the Operation
interface to a circuit as a single instruction, though most things you will want to add will be Instruction
or Gate
instances.
Operations, instructions and gates
The qiskit.circuit
level documentation on the different interfaces that Qiskit uses to define circuitlevel instructions.
Methods to add general operations
These are the base methods that handle adding any object, including userdefined ones, onto circuits.
Method  When to use it 

append()  Add an instruction as a single object onto a circuit. 
_append()  Same as append() , but a lowlevel interface that elides almost all error checking. 
compose()  Inline the instructions from one circuit onto another. 
tensor()  Like compose() , but strictly for joining circuits that act on disjoint qubits. 
QuantumCircuit
has two main ways that you will add more operations onto a circuit. Which to use depends on whether you want to add your object as a single “instruction” (append()
), or whether you want to join the instructions from two circuits together (compose()
).
A single instruction or operation appears as a single entry in the data
of the circuit, and as a single box when drawn in the circuit visualizers (see draw()
). A single instruction is the “unit” that a hardware backend might be defined in terms of (see Target
). An Instruction
can come with a definition
, which is one rule the transpiler (see qiskit.transpiler
) will be able to fall back on to decompose it for hardware, if needed. An Operation
that is not also an Instruction
can only be decomposed if it has some associated highlevel synthesis method registered for it (see qiskit.transpiler.passes.synthesis.plugin
).
A QuantumCircuit
alone is not a single Instruction
; it is rather more complicated, since it can, in general, represent a complete program with typed classical memory inputs and outputs, and control flow. Qiskit’s (and most hardware’s) data model does not yet have the concept of reusable callable subroutines with virtual quantum operands. You can convert simple circuits that act only on qubits with unitary operations into a Gate
using to_gate()
, and simple circuits acting only on qubits and clbits into a Instruction
with to_instruction()
.
When you have an Operation
, Instruction
, or Gate
, add it to the circuit, specifying the qubit and clbit arguments with append()
.
append
append(instruction, qargs=None, cargs=None, *, copy=True)
Append one or more instructions to the end of the circuit, modifying the circuit in place.
The qargs
and cargs
will be expanded and broadcast according to the rules of the given Instruction
, and any nonBit
specifiers (such as integer indices) will be resolved into the relevant instances.
If a CircuitInstruction
is given, it will be unwrapped, verified in the context of this circuit, and a new object will be appended to the circuit. In this case, you may not pass qargs
or cargs
separately.
Parameters
 instruction (Operation CircuitInstruction) –
Instruction
instance to append, or aCircuitInstruction
with all its context.  qargs (Sequence[QubitSpecifier]  None) – specifiers of the
Qubit
s to attach instruction to.  cargs (Sequence[ClbitSpecifier]  None) – specifiers of the
Clbit
s to attach instruction to.  copy (bool) – if
True
(the default), then the incominginstruction
is copied before adding it to the circuit if it contains symbolic parameters, so it can be safely mutated without affecting other circuits the same instruction might be in. If you are sure this instruction will not be in other circuits, you can set thisFalse
for a small speedup.
Returns
a handle to the CircuitInstruction
s that were actually added to the circuit.
Return type
Raises
CircuitError – if the operation passed is not an instance of Instruction
.
append()
does quite substantial error checking to ensure that you cannot accidentally break the data model of QuantumCircuit
. If you are programmatically generating a circuit from knowngood data, you can elide much of this error checking by using the fastpath appender _append()
, but at the risk that the caller is responsible for ensuring they are passing only valid data.
_append
_append(instruction: CircuitInstruction, *, _standard_gate: bool) → CircuitInstruction
_append(instruction: Operation, qargs: Sequence[Qubit], cargs: Sequence[Clbit]) → Operation
Append an instruction to the end of the circuit, modifying the circuit in place.
This is an internal fastpath function, and it is the responsibility of the caller to ensure that all the arguments are valid; there is no error checking here. In particular:
 all the qubits and clbits must already exist in the circuit and there can be no duplicates in the list.
 any controlflow operations or classically conditioned instructions must act only on variables present in the circuit.
 the circuit must not be within a controlflow builder context.
This function may be used by callers other than QuantumCircuit
when the caller is sure that all errorchecking, broadcasting and scoping has already been performed, and the only reference to the circuit the instructions are being appended to is within that same function. In particular, it is not safe to call QuantumCircuit._append()
on a circuit that is received by a function argument. This is because QuantumCircuit._append()
will not recognize the scoping constructs of the controlflow builder interface.
Parameters

instruction –
A complete wellformed
CircuitInstruction
of the operation and its context to be added.In the legacy compatibility form, this can be a bare
Operation
, in which caseqargs
andcargs
must be explicitly given. 
qargs – Legacy argument for qubits to attach the bare
Operation
to. Ignored if the first argument is in the preferentialCircuitInstruction
form. 
cargs – Legacy argument for clbits to attach the bare
Operation
to. Ignored if the first argument is in the preferentialCircuitInstruction
form.
Returns
a handle to the instruction that was just added.
Return type
In other cases, you may want to join two circuits together, applying the instructions from one circuit onto specified qubits and clbits on another circuit. This “inlining” operation is called compose()
in Qiskit. compose()
is, in general, more powerful than a to_instruction()
plusappend()
combination for joining two circuits, because it can also link typed classical data together, and allows for circuit controlflow operations to be joined onto another circuit.
The downsides to compose()
are that it is a more complex operation that can involve more rewriting of the operand, and that it necessarily must move data from one circuit object to another. If you are building up a circuit for yourself and raw performance is a core goal, consider passing around your base circuit and having different parts of your algorithm write directly to the base circuit, rather than building a temporary layer circuit.
compose
compose(other, qubits=None, clbits=None, front=False, inplace=False, wrap=False, *, copy=True, var_remap=None, inline_captures=False)
Apply the instructions from one circuit onto specified qubits and/or clbits on another.
By default, this creates a new circuit object, leaving self
untouched. For most uses of this function, it is far more efficient to set inplace=True
and modify the base circuit inplace.
When dealing with realtime variables (expr.Var
instances), there are two principal strategies for using compose()
:
 The
other
circuit is treated as entirely additive, including its variables. The variables inother
must be entirely distinct from those inself
(usevar_remap
to help with this), and all variables inother
will be declared anew in the output with matching input/capture/local scoping to how they are inother
. This is generally what you want if you’re joining two unrelated circuits.  The
other
circuit was created as an exact extension toself
to be inlined onto it, including acting on the existing variables in their states at the end ofself
. In this case,other
should be created with all these variables to be inlined declared as “captures”, and then you can useinline_captures=True
in this method to link them. This is generally what you want if you’re building up a circuit by defining layers onthefly, or rebuilding a circuit using layers taken from itself. You might find thevars_mode="captures"
argument tocopy_empty_like()
useful to create each layer’s base, in this case.
Parameters

other (qiskit.circuit.Instruction orQuantumCircuit) – (sub)circuit or instruction to compose onto self. If not a
QuantumCircuit
, this can be anything thatappend
will accept. 
front (bool) – If
True
, front composition will be performed. This is not possible within controlflow builder context managers. 
inplace (bool) – If
True
, modify the object. Otherwise, return composed circuit. 
copy (bool) – If
True
(the default), then the input is treated as shared, and any contained instructions will be copied, if they might need to be mutated in the future. You can set this toFalse
if the input should be considered owned by the base circuit, in order to avoid unnecessary copies; in this case, it is not valid to useother
afterward, and some instructions may have been mutated in place. 
var_remap (Mapping) –
mapping to use to rewrite
expr.Var
nodes inother
as they are inlined intoself
. This can be used to avoid naming conflicts.Both keys and values can be given as strings or direct
expr.Var
instances. If a key is a string, it matches anyVar
with the same name. If a value is a string, whenever a new key matches a it, a newVar
is created with the correct type. If a value is aVar
, itstype
must exactly match that of the variable it is replacing. 
inline_captures (bool) –
if
True
, then all “captured”Var
nodes in theother
QuantumCircuit
are assumed to refer to variables already declared inself
(as any input/capture/local type), and the uses inother
will apply to the existing variables. If you want to build up a layer for an existing circuit to use withcompose()
, you might find thevars_mode="captures"
argument tocopy_empty_like()
useful. Any remapping invars_remap
occurs before evaluating this variable inlining.If this is
False
(the default), then all variables inother
will be required to be distinct from those inself
, and new declarations will be made for them. 
wrap (bool) – If True, wraps the other circuit into a gate (or instruction, depending on whether it contains only unitary instructions) before composing it onto self. Rather than using this option, it is almost always better to manually control this yourself by using
to_instruction()
orto_gate()
, and then callappend()
.
Returns
the composed circuit (returns None if inplace==True).
Return type
Raises
 CircuitError – if no correct wire mapping can be made between the two circuits, such as if
other
is wider thanself
.  CircuitError – if trying to emit a new circuit while
self
has a partially built controlflow context active, such as the contextmanager forms ofif_test()
,for_loop()
andwhile_loop()
.  CircuitError – if trying to compose to the front of a circuit when a controlflow builder block is active; there is no clear meaning to this action.
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 ═══════════════════════
If you are trying to join two circuits that will apply to completely disjoint qubits and clbits, tensor()
is a convenient wrapper around manually adding bit objects and calling compose()
.
tensor
tensor(other, inplace=False)
Tensor self
with other
.
Remember that in the littleendian convention the leftmost operation will be at the bottom of the circuit. See also the docs for more information.
┌────────┐ ┌─────┐ ┌─────┐
q_0: ┤ bottom ├ ⊗ q_0: ┤ top ├ = q_0: ─┤ top ├──
└────────┘ └─────┘ ┌┴─────┴─┐
q_1: ┤ bottom ├
└────────┘
Parameters
 other (QuantumCircuit) – The other circuit to tensor this circuit with.
 inplace (bool) – If
True
, modify the object. Otherwise return composed circuit.
Return type
QuantumCircuit  None
Examples
from qiskit import QuantumCircuit
top = QuantumCircuit(1)
top.x(0);
bottom = QuantumCircuit(2)
bottom.cry(0.2, 0, 1);
tensored = bottom.tensor(top)
tensored.draw('mpl')
Returns
The tensored circuit (returns None
if inplace=True
).
Return type
As some rules of thumb:
 If you have a single
Operation
,Instruction
orGate
, you should definitely useappend()
or_append()
.  If you have a
QuantumCircuit
that represents a single atomic instruction for a larger circuit that you want to reuse, you probably want to callto_instruction()
orto_gate()
, and then apply the result of that to the circuit usingappend()
.  If you have a
QuantumCircuit
that represents a larger “layer” of another circuit, or contains typed classical variables or control flow, you should usecompose()
to merge it onto another circuit. tensor()
is wanted far more rarely than eitherappend()
orcompose()
. Internally, it is mostly a wrapper aroundadd_bits()
andcompose()
.
Some potential pitfalls to beware of:
 Even if you reuse a custom
Instruction
during circuit construction, the transpiler will generally have to “unroll” each invocation of it to its inner decomposition before beginning work on it. This should not prevent you from using theto_instruction()
plusappend()
pattern, as the transpiler will improve in this regard over time. compose()
will, by default, produce a new circuit for backwards compatibility. This is more expensive, and not usually what you want, so you should setinplace=True
. Both
append()
andcompose()
(but not_append()
) have acopy
keyword argument that defaults toTrue
. In these cases, the incomingOperation
instances will be copied if Qiskit detects that the objects have mutability about them (such as taking gate parameters). If you are sure that you will not reuse the objects again in other places, you should setcopy=False
to prevent this copying, which can be a substantial speedup for large objects.
Methods to add standard instructions
The QuantumCircuit
class has helper methods to add many of the Qiskit standardlibrary instructions and gates onto a circuit. These are generally equivalent to manually constructing an instance of the relevent qiskit.circuit.library
object, then passing that to append()
with the remaining arguments placed into the qargs
and cargs
fields as appropriate.
The following methods apply special nonunitary Instruction
operations to the circuit:
QuantumCircuit method  qiskit.circuit Instruction 

barrier()  Barrier 
delay()  Delay 
initialize()  Initialize 
measure()  Measure 
reset()  Reset 
store()  Store 
These methods apply uncontrolled unitary Gate
instances to the circuit:
The following methods apply Gate
instances that are also controlled gates, so are direct subclasses of ControlledGate
:
Finally, these methods apply particular generalized multiply controlled gates to the circuit, often with eager syntheses. They are listed in terms of the base gate they are controlling, since their exact output is often a synthesized version of a gate.
QuantumCircuit method  Base qiskit.circuit.library Gate 

mcp()  PhaseGate 
mcrx()  RXGate 
mcry()  RYGate 
mcrz()  RZGate 
mcx()  XGate 
The rest of this section is the API listing of all the individual methods; the tables above are summaries whose links will jump you to the correct place.
barrier
barrier(*qargs, label=None)
Apply Barrier
. If qargs
is empty, applies to all qubits in the circuit.
Parameters
 qargs (QubitSpecifier) – Specification for one or more qubit arguments.
 label (str) – The string label of the barrier.
Returns
handle to the added instructions.
Return type
ccx
ccx(control_qubit1, control_qubit2, target_qubit, ctrl_state=None)
Apply CCXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit1 (QubitSpecifier) – The qubit(s) used as the first control.
 control_qubit2 (QubitSpecifier) – The qubit(s) used as the second control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
ccz
ccz(control_qubit1, control_qubit2, target_qubit, label=None, ctrl_state=None)
Apply CCZGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit1 (QubitSpecifier) – The qubit(s) used as the first control.
 control_qubit2 (QubitSpecifier) – The qubit(s) used as the second control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘10’). Defaults to controlling on the ‘11’ state.
Returns
A handle to the instructions created.
Return type
ch
ch(control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CHGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
cp
cp(theta, control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CPhaseGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterValueType) – The angle of the rotation.
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
crx
crx(theta, control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CRXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterValueType) – The angle of the rotation.
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
cry
cry(theta, control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CRYGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterValueType) – The angle of the rotation.
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
crz
crz(theta, control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CRZGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterValueType) – The angle of the rotation.
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
cs
cs(control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CSGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
csdg
csdg(control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CSdgGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
cswap
cswap(control_qubit, target_qubit1, target_qubit2, label=None, ctrl_state=None)
Apply CSwapGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit1 (QubitSpecifier) – The qubit(s) targeted by the gate.
 target_qubit2 (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g.
'1'
). Defaults to controlling on the'1'
state.
Returns
A handle to the instructions created.
Return type
csx
csx(control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CSXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
cu
cu(theta, phi, lam, gamma, control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CUGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterValueType) – The $\theta$ rotation angle of the gate.
 phi (ParameterValueType) – The $\phi$ rotation angle of the gate.
 lam (ParameterValueType) – The $\lambda$ rotation angle of the gate.
 gamma (ParameterValueType) – The global phase applied of the U gate, if applied.
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
cx
cx(control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit (QubitSpecifier) – The qubit(s) used as the control.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
cy
cy(control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CYGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit (QubitSpecifier) – The qubit(s) used as the controls.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
cz
cz(control_qubit, target_qubit, label=None, ctrl_state=None)
Apply CZGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit (QubitSpecifier) – The qubit(s) used as the controls.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 label (str  None) – The string label of the gate in the circuit.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
dcx
dcx(qubit1, qubit2)
Apply DCXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
 qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
delay
delay(duration, qarg=None, unit='dt')
Apply Delay
. If qarg is None
, applies to all qubits. When applying to multiple qubits, delays with the same duration will be created.
Parameters
 duration (int orfloat orParameterExpression) – duration of the delay.
 qarg (Object) – qubit argument to apply this delay.
 unit (str) – unit of the duration. Supported units:
's'
,'ms'
,'us'
,'ns'
,'ps'
, and'dt'
. Default is'dt'
, i.e. integer time unit depending on the target backend.
Returns
handle to the added instructions.
Return type
Raises
CircuitError – if arguments have bad format.
ecr
ecr(qubit1, qubit2)
Apply ECRGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubits to apply the gate to.
 qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubits to apply the gate to.
Returns
A handle to the instructions created.
Return type
h
h(qubit)
Apply HGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
id
id(qubit)
Apply IGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
initialize
initialize(params, qubits=None, normalize=False)
Initialize qubits in a specific state.
Qubit initialization is done by first resetting the qubits to $0\rangle$ followed by calling StatePreparation
class to prepare the qubits in a specified state. Both these steps are included in the Initialize
instruction.
Parameters

params (Statevector  Sequence[complex]  str int) –
The state to initialize to, can be either of the following.
 Statevector or vector of complex amplitudes to initialize to.
 Labels of basis states of the Pauli eigenstates Z, X, Y. See
Statevector.from_label()
. Notice the order of the labels is reversed with respect to the qubit index to be applied to. Example label'01'
initializes the qubit zero to $1\rangle$ and the qubit one to $0\rangle$.  An integer that is used as a bitmap indicating which qubits to initialize to $1\rangle$. Example: setting params to 5 would initialize qubit 0 and qubit 2 to $1\rangle$ and qubit 1 to $0\rangle$.

qubits (Sequence[QubitSpecifier]  None) – Qubits to initialize. If
None
the initialization is applied to all qubits in the circuit. 
normalize (bool) – Whether to normalize an input array to a unit vector.
Returns
A handle to the instructions created.
Examples
Prepare a qubit in the state $(0\rangle  1\rangle) / \sqrt{2}$.
import numpy as np
from qiskit import QuantumCircuit
circuit = QuantumCircuit(1)
circuit.initialize([1/np.sqrt(2), 1/np.sqrt(2)], 0)
circuit.draw()
output:
┌──────────────────────────────┐
q_0: ┤ Initialize(0.70711,0.70711) ├
└──────────────────────────────┘
Initialize from a string two qubits in the state $10\rangle$. The order of the labels is reversed with respect to qubit index. More information about labels for basis states are in Statevector.from_label()
.
import numpy as np
from qiskit import QuantumCircuit
circuit = QuantumCircuit(2)
circuit.initialize('01', circuit.qubits)
circuit.draw()
output:
┌──────────────────┐
q_0: ┤0 ├
│ Initialize(0,1) │
q_1: ┤1 ├
└──────────────────┘
Initialize two qubits from an array of complex amplitudes.
import numpy as np
from qiskit import QuantumCircuit
circuit = QuantumCircuit(2)
circuit.initialize([0, 1/np.sqrt(2), 1.j/np.sqrt(2), 0], circuit.qubits)
circuit.draw()
output:
┌────────────────────────────────────┐
q_0: ┤0 ├
│ Initialize(0,0.70711,0.70711j,0) │
q_1: ┤1 ├
└────────────────────────────────────┘
iswap
iswap(qubit1, qubit2)
Apply iSwapGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubits to apply the gate to.
 qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubits to apply the gate to.
Returns
A handle to the instructions created.
Return type
mcp
mcp(lam, control_qubits, target_qubit, ctrl_state=None)
Apply MCPhaseGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 lam (ParameterValueType) – The angle of the rotation.
 control_qubits (Sequence[QubitSpecifier]) – The qubits used as the controls.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Return type
mcrx
mcrx(theta, q_controls, q_target, use_basis_gates=False)
Apply MultipleControlled X rotation gate
Parameters
 self (QuantumCircuit) – The QuantumCircuit object to apply the mcrx gate on.
 theta (float) – angle theta
 q_controls (QuantumRegister orlist(Qubit)) – The list of control qubits
 q_target (Qubit) – The target qubit
 use_basis_gates (bool) – use p, u, cx
Raises
QiskitError – parameter errors
mcry
mcry(theta, q_controls, q_target, q_ancillae=None, mode=None, use_basis_gates=False)
Apply MultipleControlled 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 ortuple(QuantumRegister, int)) – The list of ancillary qubits.
 mode (string) – The implementation mode to use
 use_basis_gates (bool) – use p, u, cx
Raises
QiskitError – parameter errors
mcrz
mcrz(lam, q_controls, q_target, use_basis_gates=False)
Apply MultipleControlled 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 p, u, cx
Raises
QiskitError – parameter errors
mcx
mcx(control_qubits, target_qubit, ancilla_qubits=None, mode='noancilla', ctrl_state=None)
Apply MCXGate
.
The multicX gate can be implemented using different techniques, which use different numbers of ancilla qubits and have varying circuit depth. These modes are:
'noancilla'
: Requires 0 ancilla qubits.'recursion'
: Requires 1 ancilla qubit if more than 4 controls are used, otherwise 0.'vchain'
: Requires 2 less ancillas than the number of control qubits.'vchaindirty'
: Same as for the clean ancillas (but the circuit will be longer).
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubits (Sequence[QubitSpecifier]) – The qubits used as the controls.
 target_qubit (QubitSpecifier) – The qubit(s) targeted by the gate.
 ancilla_qubits (QubitSpecifier  Sequence[QubitSpecifier]  None) – The qubits used as the ancillae, if the mode requires them.
 mode (str) – The choice of mode, explained further above.
 ctrl_state (str int  None) – The control state in decimal, or as a bitstring (e.g. ‘1’). Defaults to controlling on the ‘1’ state.
Returns
A handle to the instructions created.
Raises
 ValueError – if the given mode is not known, or if too few ancilla qubits are passed.
 AttributeError – if no ancilla qubits are passed, but some are needed.
Return type
measure
measure(qubit, cbit)
Measure a quantum bit (qubit
) in the Z basis into a classical bit (cbit
).
When a quantum state is measured, a qubit is projected in the computational (Pauli Z) basis to either $\lvert 0 \rangle$ or $\lvert 1 \rangle$. The classical bit cbit
indicates the result of that projection as a 0
or a 1
respectively. This operation is nonreversible.
Parameters
 qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – qubit(s) to measure.
 cbit (Clbit ClassicalRegister int slice Sequence[Clbit int]) – classical bit(s) to place the measurement result(s) in.
Returns
handle to the added instructions.
Return type
Raises
CircuitError – if arguments have bad format.
Examples
In this example, a qubit is measured and the result of that measurement is stored in the classical bit (usually expressed in diagrams as a double line):
from qiskit import QuantumCircuit
circuit = QuantumCircuit(1, 1)
circuit.h(0)
circuit.measure(0, 0)
circuit.draw()
┌───┐┌─┐
q: ┤ H ├┤M├
└───┘└╥┘
c: 1/══════╩═
0
It is possible to call measure
with lists of qubits
and cbits
as a shortcut for onetoone measurement. These two forms produce identical results:
circuit = QuantumCircuit(2, 2)
circuit.measure([0,1], [0,1])
circuit = QuantumCircuit(2, 2)
circuit.measure(0, 0)
circuit.measure(1, 1)
Instead of lists, you can use QuantumRegister
and ClassicalRegister
under the same logic.
from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister
qreg = QuantumRegister(2, "qreg")
creg = ClassicalRegister(2, "creg")
circuit = QuantumCircuit(qreg, creg)
circuit.measure(qreg, creg)
This is equivalent to:
circuit = QuantumCircuit(qreg, creg)
circuit.measure(qreg[0], creg[0])
circuit.measure(qreg[1], creg[1])
ms
ms(theta, qubits)
Apply MSGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterExpression float) – The angle of the rotation.
 qubits (Sequence[Qubit QuantumRegister int slice Sequence[Qubit int]]) – The qubits to apply the gate to.
Returns
A handle to the instructions created.
Return type
p
p(theta, qubit)
Apply PhaseGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterExpression float) – THe angle of the rotation.
 qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
pauli
pauli(pauli_string, qubits)
Apply PauliGate
.
Parameters
 pauli_string (str) – A string representing the Pauli operator to apply, e.g. ‘XX’.
 qubits (Sequence[Qubit QuantumRegister int slice Sequence[Qubit int]]) – The qubits to apply this gate to.
Returns
A handle to the instructions created.
Return type
prepare_state
prepare_state(state, qubits=None, label=None, normalize=False)
Prepare qubits in a specific state.
This class implements a state preparing unitary. Unlike initialize()
it does not reset the qubits first.
Parameters

state (Statevector  Sequence[complex]  str int) –
The state to initialize to, can be either of the following.
 Statevector or vector of complex amplitudes to initialize to.
 Labels of basis states of the Pauli eigenstates Z, X, Y. See
Statevector.from_label()
. Notice the order of the labels is reversed with respect to the qubit index to be applied to. Example label ‘01’ initializes the qubit zero to $1\rangle$ and the qubit one to $0\rangle$.  An integer that is used as a bitmap indicating which qubits to initialize to $1\rangle$. Example: setting params to 5 would initialize qubit 0 and qubit 2 to $1\rangle$ and qubit 1 to $0\rangle$.

qubits (Sequence[QubitSpecifier]  None) – Qubits to initialize. If
None
the initialization is applied to all qubits in the circuit. 
label (str  None) – An optional label for the gate

normalize (bool) – Whether to normalize an input array to a unit vector.
Returns
A handle to the instruction that was just initialized
Return type
Examples
Prepare a qubit in the state $(0\rangle  1\rangle) / \sqrt{2}$.
import numpy as np
from qiskit import QuantumCircuit
circuit = QuantumCircuit(1)
circuit.prepare_state([1/np.sqrt(2), 1/np.sqrt(2)], 0)
circuit.draw()
output:
┌─────────────────────────────────────┐
q_0: ┤ State Preparation(0.70711,0.70711) ├
└─────────────────────────────────────┘
Prepare from a string two qubits in the state $10\rangle$. The order of the labels is reversed with respect to qubit index. More information about labels for basis states are in Statevector.from_label()
.
import numpy as np
from qiskit import QuantumCircuit
circuit = QuantumCircuit(2)
circuit.prepare_state('01', circuit.qubits)
circuit.draw()
output:
┌─────────────────────────┐
q_0: ┤0 ├
│ State Preparation(0,1) │
q_1: ┤1 ├
└─────────────────────────┘
Initialize two qubits from an array of complex amplitudes .. codeblock:
import numpy as np
from qiskit import QuantumCircuit
circuit = QuantumCircuit(2)
circuit.prepare_state([0, 1/np.sqrt(2), 1.j/np.sqrt(2), 0], circuit.qubits)
circuit.draw()
output:
┌───────────────────────────────────────────┐
q_0: ┤0 ├
│ State Preparation(0,0.70711,0.70711j,0) │
q_1: ┤1 ├
└───────────────────────────────────────────┘
r
r(theta, phi, qubit)
Apply RGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterExpression float) – The angle of the rotation.
 phi (ParameterExpression float) – The angle of the axis of rotation in the xy plane.
 qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
rcccx
rcccx(control_qubit1, control_qubit2, control_qubit3, target_qubit)
Apply RC3XGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) used as the first control.
 control_qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) used as the second control.
 control_qubit3 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) used as the third control.
 target_qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) targeted by the gate.
Returns
A handle to the instructions created.
Return type
rccx
rccx(control_qubit1, control_qubit2, target_qubit)
Apply RCCXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 control_qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) used as the first control.
 control_qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) used as the second control.
 target_qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) targeted by the gate.
Returns
A handle to the instructions created.
Return type
reset
reset(qubit)
Reset the quantum bit(s) to their default state.
Parameters
qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – qubit(s) to reset.
Returns
handle to the added instruction.
Return type
rv
rv(vx, vy, vz, qubit)
Apply RVGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Rotation around an arbitrary rotation axis $v$, where $v$ is the angle of rotation in radians.
Parameters
 vx (ParameterExpression float) – xcomponent of the rotation axis.
 vy (ParameterExpression float) – ycomponent of the rotation axis.
 vz (ParameterExpression float) – zcomponent of the rotation axis.
 qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
rx
rx(theta, qubit, label=None)
Apply RXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterValueType) – The rotation angle of the gate.
 qubit (QubitSpecifier) – The qubit(s) to apply the gate to.
 label (str  None) – The string label of the gate in the circuit.
Returns
A handle to the instructions created.
Return type
rxx
rxx(theta, qubit1, qubit2)
Apply RXXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterExpression float) – The angle of the rotation.
 qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
 qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
ry
ry(theta, qubit, label=None)
Apply RYGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterValueType) – The rotation angle of the gate.
 qubit (QubitSpecifier) – The qubit(s) to apply the gate to.
 label (str  None) – The string label of the gate in the circuit.
Returns
A handle to the instructions created.
Return type
ryy
ryy(theta, qubit1, qubit2)
Apply RYYGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterExpression float) – The rotation angle of the gate.
 qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
 qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
rz
rz(phi, qubit)
Apply RZGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 phi (ParameterExpression float) – The rotation angle of the gate.
 qubit (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
rzx
rzx(theta, qubit1, qubit2)
Apply RZXGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterExpression float) – The rotation angle of the gate.
 qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
 qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type
rzz
rzz(theta, qubit1, qubit2)
Apply RZZGate
.
For the full matrix form of this gate, see the underlying gate documentation.
Parameters
 theta (ParameterExpression float) – The rotation angle of the gate.
 qubit1 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
 qubit2 (Qubit QuantumRegister int slice Sequence[Qubit int]) – The qubit(s) to apply the gate to.
Returns
A handle to the instructions created.
Return type