GaussianConditionalIndependenceModel

class GaussianConditionalIndependenceModel(n_normal, normal_max_value, p_zeros, rhos, i_normal=None, i_ps=None)[source]

The Gaussian Conditional Independence Model for Credit Risk.

Reference: https://arxiv.org/abs/1412.1183

Dependency between individual risk variables and latent variable is approximated linearly.

Parameters

  • n_normal (int) – Number of qubits to represent the latent normal random variable Z

  • normal_max_value (float) – Min/max value to truncate the latent normal random variable Z

  • p_zeros (Union[List[float], ndarray]) – Standard default probabilities for each asset

  • rhos (Union[List[float], ndarray]) – Sensitivities of default probability of assets with respect to latent variable Z

  • i_normal (Union[List[float], ndarray, None]) – Indices of qubits to represent normal variable

  • i_ps (Union[List[float], ndarray, None]) – Indices of qubits to represent asset defaults

Attributes

GaussianConditionalIndependenceModel.dimension

returns dimensions

GaussianConditionalIndependenceModel.high

returns high

GaussianConditionalIndependenceModel.low

returns low

GaussianConditionalIndependenceModel.num_qubits

returns num qubits

GaussianConditionalIndependenceModel.num_target_qubits

Returns the number of target qubits

GaussianConditionalIndependenceModel.num_values

returns number of values

GaussianConditionalIndependenceModel.probabilities

returns probabilities

GaussianConditionalIndependenceModel.probabilities_vector

returns probabilities vector

GaussianConditionalIndependenceModel.values

returns values

Methods

GaussianConditionalIndependenceModel.build(qc, q)

GaussianConditionalIndependenceModel.build_controlled(qc, …)

Adds corresponding controlled sub-circuit to given circuit

GaussianConditionalIndependenceModel.build_controlled_inverse(qc, …)

Adds controlled inverse of corresponding sub-circuit to given circuit

GaussianConditionalIndependenceModel.build_controlled_inverse_power(qc, …)

Adds controlled, inverse, power of corresponding circuit.

GaussianConditionalIndependenceModel.build_controlled_power(qc, …)

Adds controlled power of corresponding circuit.

GaussianConditionalIndependenceModel.build_inverse(qc, q)

Adds inverse of corresponding sub-circuit to given circuit

GaussianConditionalIndependenceModel.build_inverse_power(qc, …)

Adds inverse power of corresponding circuit.

GaussianConditionalIndependenceModel.build_power(qc, …)

Adds power of corresponding circuit.

GaussianConditionalIndependenceModel.get_num_qubits()

returns number of qubits

GaussianConditionalIndependenceModel.get_num_qubits_controlled()

returns number of qubits controlled

GaussianConditionalIndependenceModel.pdf_to_probabilities(…)

pdf to probabilities

GaussianConditionalIndependenceModel.required_ancillas()

returns required ancillas

GaussianConditionalIndependenceModel.required_ancillas_controlled()

returns required ancillas controlled