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qiskit.aqua.components.uncertainty_models.LogNormalDistribution

class LogNormalDistribution(num_target_qubits, mu=0, sigma=1, low=0, high=1)

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The Univariate Log-Normal Distribution.

Log-normal distribution, truncated to lower and upper bound and discretized on a grid defined by the number of qubits.

Parameters

  • num_target_qubits (int) – Number of qubits it acts on, has a minimum value of 1.
  • mu (float) – Expected value of considered normal distribution
  • sigma (float) – Standard deviation of considered normal distribution
  • low (float) – Lower bound, i.e., the value corresponding to |0…0> (assuming an equidistant grid)
  • high (float) – Upper bound, i.e., the value corresponding to |1…1> (assuming an equidistant grid)

__init__

__init__(num_target_qubits, mu=0, sigma=1, low=0, high=1)

Parameters

  • num_target_qubits (int) – Number of qubits it acts on, has a minimum value of 1.
  • mu (float) – Expected value of considered normal distribution
  • sigma (float) – Standard deviation of considered normal distribution
  • low (float) – Lower bound, i.e., the value corresponding to |0…0> (assuming an equidistant grid)
  • high (float) – Upper bound, i.e., the value corresponding to |1…1> (assuming an equidistant grid)

Methods

__init__(num_target_qubits[, mu, sigma, …])type num_target_qubitsint
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
pdf_to_probabilities(pdf, low, high, num_values)Takes a probability density function (pdf), and returns a truncated and discretized array of probabilities corresponding to it
required_ancillas()returns required ancillas
required_ancillas_controlled()returns required ancillas controlled

Attributes

highreturns high
lowreturns low
num_target_qubitsReturns the number of target qubits
num_valuesreturns number of values
probabilitiesreturns probabilities
valuesreturns values

build

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

build_controlled

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

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

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

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

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

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

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

get_num_qubits()

returns number of qubits

get_num_qubits_controlled

get_num_qubits_controlled()

returns number of qubits controlled

high

returns high

low

returns low

num_target_qubits

Returns the number of target qubits

num_values

returns number of values

pdf_to_probabilities

static pdf_to_probabilities(pdf, low, high, num_values)

Takes a probability density function (pdf), and returns a truncated and discretized array of probabilities corresponding to it

Parameters

  • pdf (function) – probability density function
  • low (float) – lower bound of equidistant grid
  • high (float) – upper bound of equidistant grid
  • num_values (int) – number of grid points

Returns

array of probabilities

Return type

list

probabilities

returns probabilities

required_ancillas

required_ancillas()

returns required ancillas

required_ancillas_controlled

required_ancillas_controlled()

returns required ancillas controlled

values

returns values

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