class qiskit.circuit.library.VBERippleCarryAdder(num_state_qubits, kind='full', name='VBERippleCarryAdder')[source]#

Bases : Adder

The VBE ripple carry adder [1].

This circuit performs inplace addition of two equally-sized quantum registers. As an example, a classical adder circuit that performs full addition (i.e. including a carry-in bit) on two 2-qubit sized registers is as follows:

          β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”                       β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”β”Œβ”€β”€β”€β”€β”€β”€β”
   cin_0: ─0       β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€0          β”œβ”€0     β”œ
          β”‚        β”‚                       β”‚           β”‚β”‚      β”‚
     a_0: ─1       β”œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€1          β”œβ”€1     β”œ
          β”‚        β”‚β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”     β”Œβ”€β”€β”€β”€β”€β”€β”β”‚           β”‚β”‚  Sum β”‚
     a_1: ─        β”œβ”€1       β”œβ”€β”€β– β”€β”€β”€1     β”œβ”€           β”œβ”€      β”œ
          β”‚        β”‚β”‚        β”‚  β”‚  β”‚      β”‚β”‚           β”‚β”‚      β”‚
     b_0: ─2 Carry β”œβ”€        β”œβ”€β”€β”Όβ”€β”€β”€      β”œβ”€2 Carry_dg β”œβ”€2     β”œ
          β”‚        β”‚β”‚        β”‚β”Œβ”€β”΄β”€β”β”‚      β”‚β”‚           β”‚β””β”€β”€β”€β”€β”€β”€β”˜
     b_1: ─        β”œβ”€2 Carry β”œβ”€ X β”œβ”€2 Sum β”œβ”€           β”œβ”€β”€β”€β”€β”€β”€β”€β”€
          β”‚        β”‚β”‚        β”‚β””β”€β”€β”€β”˜β”‚      β”‚β”‚           β”‚
  cout_0: ─        β”œβ”€3       β”œβ”€β”€β”€β”€β”€β”€      β”œβ”€           β”œβ”€β”€β”€β”€β”€β”€β”€β”€
          β”‚        β”‚β”‚        β”‚     β”‚      β”‚β”‚           β”‚
helper_0: ─3       β”œβ”€0       β”œβ”€β”€β”€β”€β”€β”€0     β”œβ”€3          β”œβ”€β”€β”€β”€β”€β”€β”€β”€
          β””β”€β”€β”€β”€β”€β”€β”€β”€β”˜β””β”€β”€β”€β”€β”€β”€β”€β”€β”˜     β””β”€β”€β”€β”€β”€β”€β”˜β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Here Carry and Sum gates correspond to the gates introduced in [1]. Carry_dg correspond to the inverse of the Carry gate. Note that in this implementation the input register qubits are ordered as all qubits from the first input register, followed by all qubits from the second input register. This is different ordering as compared to Figure 2 in [1], which leads to a different drawing of the circuit.


[1] Vedral et al., Quantum Networks for Elementary Arithmetic Operations, 1995. arXiv:quant-ph/9511018

  • num_state_qubits (int) – The size of the register.

  • kind (str) – The kind of adder, can be 'full' for a full adder, 'half' for a half adder, or 'fixed' for a fixed-sized adder. A full adder includes both carry-in and carry-out, a half only carry-out, and a fixed-sized adder neither carry-in nor carry-out.

  • name (str) – The name of the circuit.


ValueError – If num_state_qubits is lower than 1.



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


Return calibration dictionary.

The custom pulse definition of a given gate is of the form {'gate_name': {(qubits, params): schedule}}


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


Return the circuit data (instructions and context).


a list-like object containing the CircuitInstructions for each instruction.

Type renvoyΓ©:


extension_lib = 'include "qelib1.inc";'#

Return the global phase of the circuit in radians.

header = 'OPENQASM 2.0;'#
instances = 127#

Return any associated layout information about the circuit

This attribute contains an optional TranspileLayout object. This is typically set on the output from transpile() or PassManager.run() to retain information about the permutations caused on the input circuit by transpilation.

There are two types of permutations caused by the transpile() function, an initial layout which permutes the qubits based on the selected physical qubits on the Target, and a final layout which is an output permutation caused by SwapGates inserted during routing.


The user provided metadata associated with the circuit.

The metadata for the circuit is a user provided dict of metadata for the circuit. It will not be used to influence the execution or operation of the circuit, but it is expected to be passed between all transforms of the circuit (ie transpilation) and that providers will associate any circuit metadata with the results it returns from execution of that circuit.


Return the number of ancilla qubits.


Return number of classical bits.


The number of parameter objects in the circuit.


Return number of qubits.


The number of state qubits, i.e. the number of bits in each input register.


The number of state qubits.


Return a list of operation start times.

This attribute is enabled once one of scheduling analysis passes runs on the quantum circuit.


List of integers representing instruction start times. The index corresponds to the index of instruction in QuantumCircuit.data.


AttributeError – When circuit is not scheduled.


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.


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) β”œ
>>> 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
    ParameterVectorElement(x[0]), ParameterVectorElement(x[1]),
    ParameterVectorElement(x[2]), ParameterVectorElement(x[3]),
    ..., ParameterVectorElement(x[11])

The sorted Parameter objects in the circuit.

prefix = 'circuit'#

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