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CDKMRippleCarryAdder

class qiskit.circuit.library.CDKMRippleCarryAdder(num_state_qubits, kind='full', name='CDKMRippleCarryAdder')

GitHub(opens in a new tab)

Bases: Adder

A ripple-carry circuit to perform in-place addition on two qubit registers.

As an example, a ripple-carry adder circuit that performs addition on two 3-qubit sized registers with a carry-in bit (kind="full") is as follows:

        ┌──────┐                                     ┌──────┐
 cin_0:2     ├─────────────────────────────────────┤2
        │      │┌──────┐                     ┌──────┐│      │
   a_0:0     ├┤2     ├─────────────────────┤2     ├┤0
        │      ││      │┌──────┐     ┌──────┐│      ││      │
   a_1: ┤  MAJ ├┤0     ├┤2     ├─────┤2     ├┤0     ├┤  UMA ├
        │      ││      ││      │     │      ││      ││      │
   a_2: ┤      ├┤  MAJ ├┤0     ├──■──┤0     ├┤  UMA ├┤      ├
        │      ││      ││      │  │  │      ││      ││      │
   b_0:1     ├┤      ├┤  MAJ ├──┼──┤  UMA ├┤      ├┤1
        └──────┘│      ││      │  │  │      ││      │└──────┘
   b_1: ────────┤1     ├┤      ├──┼──┤      ├┤1     ├────────
                └──────┘│      │  │  │      │└──────┘
   b_2: ────────────────┤1     ├──┼──┤1     ├────────────────
                        └──────┘┌─┴─┐└──────┘
cout_0: ────────────────────────┤ X ├────────────────────────
                                └───┘

Here MAJ and UMA gates correspond to the gates introduced in [1]. 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.

Two different kinds of adders are supported. By setting the kind argument, you can also choose a half-adder, which doesn’t have a carry-in, and a fixed-sized-adder, which has neither carry-in nor carry-out, and thus acts on fixed register sizes. Unlike the full-adder, these circuits need one additional helper qubit.

The circuit diagram for the fixed-point adder (kind="fixed") on 3-qubit sized inputs is

        ┌──────┐┌──────┐                ┌──────┐┌──────┐
   a_0:0     ├┤2     ├────────────────┤2     ├┤0
        │      ││      │┌──────┐┌──────┐│      ││      │
   a_1: ┤      ├┤0     ├┤2     ├┤2     ├┤0     ├┤      ├
        │      ││      ││      ││      ││      ││      │
   a_2: ┤      ├┤  MAJ ├┤0     ├┤0     ├┤  UMA ├┤      ├
        │      ││      ││      ││      ││      ││      │
   b_0:1 MAJ ├┤      ├┤  MAJ ├┤  UMA ├┤      ├┤1 UMA ├
        │      ││      ││      ││      ││      ││      │
   b_1: ┤      ├┤1     ├┤      ├┤      ├┤1     ├┤      ├
        │      │└──────┘│      ││      │└──────┘│      │
   b_2: ┤      ├────────┤1     ├┤1     ├────────┤      ├
        │      │        └──────┘└──────┘        │      │
help_0:2     ├────────────────────────────────┤2
        └──────┘                                └──────┘

It has one less qubit than the full-adder since it doesn’t have the carry-out, but uses a helper qubit instead of the carry-in, so it only has one less qubit, not two.

References:

[1] Cuccaro et al., A new quantum ripple-carry addition circuit, 2004. arXiv:quant-ph/0410184(opens in a new tab)

[2] Vedral et al., Quantum Networks for Elementary Arithmetic Operations, 1995. arXiv:quant-ph/9511018(opens in a new tab)

Parameters

  • num_state_qubits (int(opens in a new tab)) – The number of qubits in either input register for state a|a\rangle or b|b\rangle. The two input registers must have the same number of qubits.
  • kind (str(opens in a new tab)) – 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(opens in a new tab)) – The name of the circuit object.

Raises

ValueError(opens in a new tab) – If num_state_qubits is lower than 1.


Attributes

ancillas

A list of AncillaQubits in the order that they were added. You should not mutate this.

calibrations

Return calibration dictionary.

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

clbits

A list of Clbits in the order that they were added. You should not mutate this.

data

The circuit data (instructions and context).

Returns

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

Return type

QuantumCircuitData

global_phase

The global phase of the current circuit scope in radians.

instances

Default value: 206

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 SwapGates inserted during routing.

metadata

Arbitrary user-defined metadata for the circuit.

Qiskit will not examine the content of this mapping, but it will pass it through the transpiler and reattach it to the output, so you can track your own metadata.

num_ancillas

Return the number of ancilla qubits.

num_captured_vars

The number of real-time classical variables in the circuit marked as captured from an enclosing scope.

This is the length of the iter_captured_vars() iterable. If this is non-zero, num_input_vars must be zero.

num_clbits

Return number of classical bits.

num_declared_vars

The number of real-time classical variables in the circuit that are declared by this circuit scope, excluding inputs or captures.

This is the length of the iter_declared_vars() iterable.

num_input_vars

The number of real-time classical variables in the circuit marked as circuit inputs.

This is the length of the iter_input_vars() iterable. If this is non-zero, num_captured_vars must be zero.

num_parameters

The number of parameter objects in the circuit.

num_qubits

Return number of qubits.

num_state_qubits

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

Returns

The number of state qubits.

num_vars

The number of real-time classical variables in the circuit.

This is the length of the iter_vars() iterable.

op_start_times

Return a list of operation start times.

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

Returns

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

Raises

AttributeError(opens in a new tab) – When circuit is not scheduled.

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.

prefix

Default value: 'circuit'

qubits

A list of Qubits in the order that they were added. You should not mutate this.

name

Type: str

A human-readable name for the circuit.

qregs

Type: list[QuantumRegister]

A list of the QuantumRegisters in this circuit. You should not mutate this.

cregs

Type: list[ClassicalRegister]

A list of the ClassicalRegisters in this circuit. You should not mutate this.

duration

Type: int | float | None

The total duration of the circuit, set by a scheduling transpiler pass. Its unit is specified by unit.

unit

The unit that duration is specified in.

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