MultivariateNormalDistribution

class MultivariateNormalDistribution(num_qubits, low=None, high=None, mu=None, sigma=None)

The Multivariate Normal Distribution.

Provides a discretized and truncated normal distribution loaded into a quantum state. Truncation bounds are given by lower and upper bound and discretization is specified by the number of qubits per dimension.

Parameters

• num_qubits (Union[List[int], ndarray]) – Number of qubits per dimension

• low (Union[List[float], ndarray, None]) – Lower bounds per dimension

• high (Union[List[float], ndarray, None]) – Upper bounds per dimension

• mu (Union[List[float], ndarray, None]) – Expected values

• sigma (Union[List[float], ndarray, None]) – Co-variance matrix

Attributes

MultivariateNormalDistribution.dimension	returns dimensions
MultivariateNormalDistribution.high	returns high
MultivariateNormalDistribution.low	returns low
MultivariateNormalDistribution.num_qubits	returns num qubits
MultivariateNormalDistribution.num_target_qubits	Returns the number of target qubits
MultivariateNormalDistribution.num_values	returns number of values
MultivariateNormalDistribution.probabilities	returns probabilities
MultivariateNormalDistribution.probabilities_vector	returns probabilities vector
MultivariateNormalDistribution.values	returns values

Methods

MultivariateNormalDistribution.build(qc, q)
MultivariateNormalDistribution.build_controlled(qc, …)	Adds corresponding controlled sub-circuit to given circuit
MultivariateNormalDistribution.build_controlled_inverse(qc, …)	Adds controlled inverse of corresponding sub-circuit to given circuit
MultivariateNormalDistribution.build_controlled_inverse_power(qc, …)	Adds controlled, inverse, power of corresponding circuit.
MultivariateNormalDistribution.build_controlled_power(qc, …)	Adds controlled power of corresponding circuit.
MultivariateNormalDistribution.build_inverse(qc, q)	Adds inverse of corresponding sub-circuit to given circuit
MultivariateNormalDistribution.build_inverse_power(qc, …)	Adds inverse power of corresponding circuit.
MultivariateNormalDistribution.build_power(qc, …)	Adds power of corresponding circuit.
MultivariateNormalDistribution.get_num_qubits()	returns number of qubits
MultivariateNormalDistribution.get_num_qubits_controlled()	returns number of qubits controlled
MultivariateNormalDistribution.pdf_to_probabilities(…)	pdf to probabilities
MultivariateNormalDistribution.required_ancillas()	returns required ancillas
MultivariateNormalDistribution.required_ancillas_controlled()	returns required ancillas controlled