GaussianConditionalIndependenceModel

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

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

returns dimensions

returns high

returns low

returns num qubits

Returns the number of target qubits

returns number of values

returns probabilities

returns probabilities vector

returns values

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

GaussianConditionalIndependenceModel.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

GaussianConditionalIndependenceModel.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

GaussianConditionalIndependenceModel.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

GaussianConditionalIndependenceModel.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

GaussianConditionalIndependenceModel.build_inverse(qc, q, q_ancillas=None)

Adds inverse of corresponding sub-circuit to given circuit

Parameters

GaussianConditionalIndependenceModel.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

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

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

GaussianConditionalIndependenceModel.get_num_qubits()

returns number of qubits

GaussianConditionalIndependenceModel.get_num_qubits_controlled()

returns number of qubits controlled

static GaussianConditionalIndependenceModel.pdf_to_probabilities(pdf, low, high, num_values)

pdf to probabilities

GaussianConditionalIndependenceModel.required_ancillas()

returns required ancillas

GaussianConditionalIndependenceModel.required_ancillas_controlled()

returns required ancillas controlled

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