WeightedAdder

class qiskit.circuit.library.WeightedAdder(num_state_qubits=None, weights=None, name='adder')

Bases: BlueprintCircuit

A circuit to compute the weighted sum of qubit registers.

Given $n$ qubit basis states $q_0, \ldots, q_{n-1} \in \{0, 1\}$ and non-negative integer weights $\lambda_0, \ldots, \lambda_{n-1}$ , this circuit performs the operation

|q_0 \ldots q_{n-1}\rangle |0\rangle_s \mapsto |q_0 \ldots q_{n-1}\rangle |\sum_{j=0}^{n-1} \lambda_j q_j\rangle_s

where $s$ is the number of sum qubits required. This can be computed as

s = 1 + \left\lfloor \log_2\left( \sum_{j=0}^{n-1} \lambda_j \right) \right\rfloor

or $s = 1$ if the sum of the weights is 0 (then the expression in the logarithm is invalid).

For qubits in a circuit diagram, the first weight applies to the upper-most qubit. For an example where the state of 4 qubits is added into a sum register, the circuit can be schematically drawn as

           ┌────────┐
  state_0: ┤0       ├ | state_0 * weights[0]
           │        │ |
  state_1: ┤1       ├ | + state_1 * weights[1]
           │        │ |
  state_2: ┤2       ├ | + state_2 * weights[2]
           │        │ |
  state_3: ┤3       ├ | + state_3 * weights[3]
           │        │
    sum_0: ┤4       ├ |
           │  Adder │ |
    sum_1: ┤5       ├ | = sum_0 * 2^0 + sum_1 * 2^1 + sum_2 * 2^2
           │        │ |
    sum_2: ┤6       ├ |
           │        │
  carry_0: ┤7       ├
           │        │
  carry_1: ┤8       ├
           │        │
control_0: ┤9       ├
           └────────┘

Computes the weighted sum controlled by state qubits.

Parameters

num_state_qubits (int | None) – The number of state qubits.
weights (List[int] | None) – List of weights, one for each state qubit. If none are provided they default to 1 for every qubit.
name (str) – The name of the circuit.

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: 160

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_carry_qubits

The number of carry qubits required to compute the sum.

Note that this is not necessarily equal to the number of ancilla qubits, these can be queried using num_ancilla_qubits.

Returns

The number of carry qubits required to compute the sum.

num_clbits

Return number of classical bits.

num_control_qubits

The number of additional control qubits required.

Note that the total number of ancilla qubits can be obtained by calling the method num_ancilla_qubits.

Returns

The number of additional control qubits required (0 or 1).

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 qubits to be summed.

Returns

The number of state qubits.

num_sum_qubits

The number of sum qubits in the circuit.

Returns

The number of qubits needed to represent the weighted sum of the 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'

qregs

Type: list[QuantumRegister]

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

qubits

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

weights

The weights for the qubit states.

Returns

The weight for the qubit states.

name

Type: str

A human-readable name for the circuit.

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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