UnivariateDistribution¶

class UnivariateDistribution(num_target_qubits, probabilities=None, low=0, high=1)[source]¶

This module contains the definition of a base class for univariate distributions. (Interface for discrete bounded uncertainty models assuming an equidistant grid)

Parameters

num_target_qubits (int) – Number of qubits it acts on, has a min. value of 1.
probabilities (Union[List[float], ndarray, None]) – Probabilities for different states
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)

Raises

AquaError – num qubits and length of probabilities vector do not match

Attributes

`UnivariateDistribution.high`	returns high
`UnivariateDistribution.low`	returns low
`UnivariateDistribution.num_target_qubits`	Returns the number of target qubits
`UnivariateDistribution.num_values`	returns number of values
`UnivariateDistribution.probabilities`	returns probabilities
`UnivariateDistribution.values`	returns values

Methods

`UnivariateDistribution.build`(qc, q[, …])
`UnivariateDistribution.build_controlled`(qc, …)	Adds corresponding controlled sub-circuit to given circuit
`UnivariateDistribution.build_controlled_inverse`(qc, …)	Adds controlled inverse of corresponding sub-circuit to given circuit
`UnivariateDistribution.build_controlled_inverse_power`(qc, …)	Adds controlled, inverse, power of corresponding circuit.
`UnivariateDistribution.build_controlled_power`(qc, …)	Adds controlled power of corresponding circuit.
`UnivariateDistribution.build_inverse`(qc, q)	Adds inverse of corresponding sub-circuit to given circuit
`UnivariateDistribution.build_inverse_power`(qc, …)	Adds inverse power of corresponding circuit.
`UnivariateDistribution.build_power`(qc, q, power)	Adds power of corresponding circuit.
`UnivariateDistribution.get_num_qubits`()	returns number of qubits
`UnivariateDistribution.get_num_qubits_controlled`()	returns number of qubits controlled
`UnivariateDistribution.pdf_to_probabilities`(…)	Takes a probability density function (pdf), and returns a truncated and discretized array of probabilities corresponding to it
`UnivariateDistribution.required_ancillas`()	returns required ancillas
`UnivariateDistribution.required_ancillas_controlled`()	returns required ancillas controlled