qiskit.aqua.components.uncertainty_problems.UnivariatePiecewiseLinearObjective

class UnivariatePiecewiseLinearObjective(num_state_qubits, min_state_value, max_state_value, breakpoints, slopes, offsets, f_min, f_max, c_approx, i_state=None, i_objective=None)

Univariate Piecewise Linear Objective Function.

This objective function applies controlled Y-rotation to the target qubit, where the control qubits represent integer value, and rotation approximates a piecewise linear function of the amplitude f:

\[|x\rangle |0\rangle \mapsto |x\rangle (\sqrt(1 - f(x))|0\rangle + sqrt(f(x))|1\rangle )\]

Parameters

• num_state_qubits (int) – number of qubits to represent the state

• min_state_value (float) – lower bound of values to be represented by state qubits

• max_state_value (float) – upper bound of values to be represented by state qubits

• breakpoints (Union[List[float], ndarray]) – breakpoints of piecewise linear function

• slopes (Union[List[float], ndarray]) – slopes of linear segments

• offsets (Union[List[float], ndarray]) – offset of linear segments

• f_min (float) – minimal value of resulting function (required for normalization of amplitude)

• f_max (float) – maximal value of resulting function (required for normalization of amplitude)

• c_approx (float) – approximating factor (linear segments are approximated by contracting rotation around pi/4, where sin^2() is locally linear)

• i_state (Optional[List[int]]) – indices of qubits that represent the state

• i_objective (Optional[int]) – index of target qubit to apply the rotation to

__init__(num_state_qubits, min_state_value, max_state_value, breakpoints, slopes, offsets, f_min, f_max, c_approx, i_state=None, i_objective=None)

Parameters

• num_state_qubits (int) – number of qubits to represent the state

• min_state_value (float) – lower bound of values to be represented by state qubits

• max_state_value (float) – upper bound of values to be represented by state qubits

• breakpoints (Union[List[float], ndarray]) – breakpoints of piecewise linear function

• slopes (Union[List[float], ndarray]) – slopes of linear segments

• offsets (Union[List[float], ndarray]) – offset of linear segments

• f_min (float) – minimal value of resulting function (required for normalization of amplitude)

• f_max (float) – maximal value of resulting function (required for normalization of amplitude)

• c_approx (float) – approximating factor (linear segments are approximated by contracting rotation around pi/4, where sin^2() is locally linear)

• i_state (Optional[List[int]]) – indices of qubits that represent the state

• i_objective (Optional[int]) – index of target qubit to apply the rotation to

Methods

__init__(num_state_qubits, min_state_value, …)	type num_state_qubits int
build(qc, q[, q_ancillas, params])
build_controlled(qc, q, q_control[, …])	Adds corresponding controlled sub-circuit to given circuit
build_controlled_inverse(qc, q, q_control[, …])	Adds controlled inverse of corresponding sub-circuit to given circuit
build_controlled_inverse_power(qc, q, …[, …])	Adds controlled, inverse, power of corresponding circuit.
build_controlled_power(qc, q, q_control, power)	Adds controlled power of corresponding circuit.
build_inverse(qc, q[, q_ancillas])	Adds inverse of corresponding sub-circuit to given circuit
build_inverse_power(qc, q, power[, q_ancillas])	Adds inverse power of corresponding circuit.
build_power(qc, q, power[, q_ancillas])	Adds power of corresponding circuit.
get_num_qubits()	returns number of qubits
get_num_qubits_controlled()	returns number of qubits controlled
required_ancillas()	requires ancillas
required_ancillas_controlled()	returns required ancillas controlled
value_to_estimation(value)	value to estimation

Attributes

num_target_qubits

Returns the number of target qubits

build(qc, q, q_ancillas=None, params=None)

build_controlled(qc, q, q_control, q_ancillas=None, use_basis_gates=True)

Adds corresponding controlled sub-circuit to given circuit

Parameters

• qc (QuantumCircuit) – quantum circuit

• q (list) – list of qubits (has to be same length as self._num_qubits)

• q_control (Qubit) – control qubit

• q_ancillas (list) – list of ancilla qubits (or None if none needed)

• use_basis_gates (bool) – use basis gates for expansion of controlled circuit

build_controlled_inverse(qc, q, q_control, q_ancillas=None, use_basis_gates=True)

Adds controlled inverse of corresponding sub-circuit to given circuit

Parameters

• qc (QuantumCircuit) – quantum circuit

• q (list) – list of qubits (has to be same length as self._num_qubits)

• q_control (Qubit) – control qubit

• q_ancillas (list) – list of ancilla qubits (or None if none needed)

• use_basis_gates (bool) – use basis gates for expansion of controlled circuit

build_controlled_inverse_power(qc, q, q_control, power, q_ancillas=None, use_basis_gates=True)

Adds controlled, inverse, power of corresponding circuit. May be overridden if a more efficient implementation is possible

build_controlled_power(qc, q, q_control, power, q_ancillas=None, use_basis_gates=True)

Adds controlled power of corresponding circuit. May be overridden if a more efficient implementation is possible

build_inverse(qc, q, q_ancillas=None)

Adds inverse of corresponding sub-circuit to given circuit

Parameters

• qc (QuantumCircuit) – quantum circuit

• q (list) – list of qubits (has to be same length as self._num_qubits)

• q_ancillas (list) – list of ancilla qubits (or None if none needed)

build_inverse_power(qc, q, power, q_ancillas=None)

Adds inverse power of corresponding circuit. May be overridden if a more efficient implementation is possible

build_power(qc, q, power, q_ancillas=None)

Adds power of corresponding circuit. May be overridden if a more efficient implementation is possible

get_num_qubits()

returns number of qubits

get_num_qubits_controlled()

returns number of qubits controlled

property num_target_qubits

Returns the number of target qubits

required_ancillas()

requires ancillas

required_ancillas_controlled()

returns required ancillas controlled

value_to_estimation(value)

value to estimation