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PiecewisePolynomialPauliRotations

class qiskit.circuit.library.PiecewisePolynomialPauliRotations(num_state_qubits=None, breakpoints=None, coeffs=None, basis='Y', name='pw_poly')

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Bases: FunctionalPauliRotations

Piecewise-polynomially-controlled Pauli rotations.

This class implements a piecewise polynomial (not necessarily continuous) function, f(x)f(x), on qubit amplitudes, which is defined through breakpoints and coefficients as follows. Suppose the breakpoints (x0,...,xJ)(x_0, ..., x_J) are a subset of [0,2n−1][0, 2^n-1], where nn is the number of state qubits. Further on, denote the corresponding coefficients by [aj,1,...,aj,d][a_{j,1},...,a_{j,d}], where dd is the highest degree among all polynomials.

Then f(x)f(x) is defined as:

f(x)={0,x<x0∑i=0i=daj,i/2xi,xj≤x<xj+1f(x) = \begin{cases} 0, x < x_0 \\ \sum_{i=0}^{i=d}a_{j,i}/2 x^i, x_j \leq x < x_{j+1} \end{cases}

where if given the same number of breakpoints as polynomials, we implicitly assume xJ+1=2nx_{J+1} = 2^n.

Note

Note the 1/21/2 factor in the coefficients of f(x)f(x), this is consistent with Qiskit’s Pauli rotations.

Examples

>>> from qiskit import QuantumCircuit
>>> from qiskit.circuit.library.arithmetic.piecewise_polynomial_pauli_rotations import\
... PiecewisePolynomialPauliRotations
>>> qubits, breakpoints, coeffs = (2, [0, 2], [[0, -1.2],[-1, 1, 3]])
>>> poly_r = PiecewisePolynomialPauliRotations(num_state_qubits=qubits,
...breakpoints=breakpoints, coeffs=coeffs)
>>>
>>> qc = QuantumCircuit(poly_r.num_qubits)
>>> qc.h(list(range(qubits)));
>>> qc.append(poly_r.to_instruction(), list(range(qc.num_qubits)));
>>> qc.draw()
     ┌───┐┌──────────┐
q_0: ┤ H ├┤0         ├
     ├───┤│          │
q_1: ┤ H ├┤1         ├
     └───┘│          │
q_2: ─────┤2         ├
          │  pw_poly │
q_3: ─────┤3         ├
          │          │
q_4: ─────┤4         ├
          │          │
q_5: ─────┤5         ├
          └──────────┘

References

[1]: Haener, T., Roetteler, M., & Svore, K. M. (2018).

Optimizing Quantum Circuits for Arithmetic. arXiv:1805.12445

[2]: Carrera Vazquez, A., Hiptmair, R., & Woerner, S. (2022).

Enhancing the Quantum Linear Systems Algorithm using Richardson Extrapolation. ACM Transactions on Quantum Computing 3, 1, Article 2

Parameters

  • num_state_qubits (Optional[int]) – The number of qubits representing the state.
  • breakpoints (Optional[List[int]]) – The breakpoints to define the piecewise-linear function. Defaults to [0].
  • coeffs (Optional[List[List[float]]]) – The coefficients of the polynomials for different segments of the
  • x (piecewise-linear function. coeffs[j][i] is the coefficient of the i-th power of) –
  • polynomial. (for the j-th) – Defaults to linear: [[1]].
  • basis (str) – The type of Pauli rotation ('X', 'Y', 'Z').
  • 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.

basis

The kind of Pauli rotation to be used.

Set the basis to ‘X’, ‘Y’ or ‘Z’ for controlled-X, -Y, or -Z rotations respectively.

Returns

The kind of Pauli rotation used in controlled rotation.

breakpoints

The breakpoints of the piecewise polynomial function.

The function is polynomial in the intervals [point_i, point_{i+1}] where the last point implicitly is 2**(num_state_qubits + 1).

Returns

The list of breakpoints.

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.

coeffs

The coefficients of the polynomials.

Returns

The polynomial coefficients per interval as nested lists.

contains_zero_breakpoint

Whether 0 is the first breakpoint.

Returns

True, if 0 is the first breakpoint, otherwise False.

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: 256

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.

mapped_coeffs

The coefficients mapped to the internal representation, since we only compare x>=breakpoint.

Returns

The mapped coefficients.

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_ancilla_qubits

The minimum number of ancilla qubits in the circuit.

Returns

The minimal number of ancillas required.

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 representing the state ∣x⟩|x\rangle.

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'

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.

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.

Methods

evaluate

evaluate(x)

GitHub

Classically evaluate the piecewise polynomial rotation.

Parameters

x (float) – Value to be evaluated at.

Returns

Value of piecewise polynomial function at x.

Return type

float

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