CDKMRippleCarryAdder
class qiskit.circuit.library.CDKMRippleCarryAdder(num_state_qubits, kind='full', name='CDKMRippleCarryAdder')
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.
The following generic gate objects perform additions, like this circuit class, but allow the compiler to select the optimal decomposition based on the context. Specific implementations can be set via the HLSConfig, e.g. this circuit can be chosen via Adder=["ripple_c04"].
ModularAdderGate: A generic inplace adder, modulo . This
is functionally equivalent to kind="fixed".
AdderGate: A generic inplace adder. This
is functionally equivalent to kind="half".
FullAdderGate: A generic inplace adder, with a carry-in bit. This
is functionally equivalent to kind="full".
References:
[1] Cuccaro et al., A new quantum ripple-carry addition circuit, 2004. arXiv:quant-ph/0410184
[2] Vedral et al., Quantum Networks for Elementary Arithmetic Operations, 1995. arXiv:quant-ph/9511018
Parameters
- num_state_qubits (int) – The number of qubits in either input register for state or . The two input registers must have the same number of qubits.
- 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 object.
Raises
ValueError – 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}}
The property qiskit.circuit.quantumcircuit.QuantumCircuit.calibrations is deprecated as of Qiskit 1.3. It will be removed in Qiskit 2.0. The entire Qiskit Pulse package is being deprecated and will be moved to the Qiskit Dynamics repository: https://github.com/qiskit-community/qiskit-dynamics. Note that once removed, qiskit.circuit.quantumcircuit.QuantumCircuit.calibrations will have no alternative in Qiskit.
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
duration
The total duration of the circuit, set by a scheduling transpiler pass. Its unit is specified by unit.
The property qiskit.circuit.quantumcircuit.QuantumCircuit.duration is deprecated as of Qiskit 1.3.0. It will be removed in Qiskit 2.0.0.
global_phase
The global phase of the current circuit scope in radians.
instances
Default value: 193
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 – 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.
unit
The unit that duration is specified in.
The property qiskit.circuit.quantumcircuit.QuantumCircuit.unit is deprecated as of Qiskit 1.3.0. It will be removed in Qiskit 2.0.0.
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.