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BernoulliDistribution

class BernoulliDistribution(p, low=0, high=1)

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The Univariate Bernoulli Distribution.

Distribution with only two values (low, high) and the corresponding probabilities represented by a single qubit.

Parameters

  • p (float) – Probability
  • low (float) – Low value
  • high (float) – High value

Attributes

high

returns high

low

returns low

num_target_qubits

Returns the number of target qubits

num_values

returns number of values

p

probabilities

returns probabilities

values

returns values


Methods

build

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

build_controlled

BernoulliDistribution.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

BernoulliDistribution.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

BernoulliDistribution.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

BernoulliDistribution.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

BernoulliDistribution.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

BernoulliDistribution.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

BernoulliDistribution.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

BernoulliDistribution.get_num_qubits()

returns number of qubits

get_num_qubits_controlled

BernoulliDistribution.get_num_qubits_controlled()

returns number of qubits controlled

pdf_to_probabilities

static BernoulliDistribution.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

required_ancillas

BernoulliDistribution.required_ancillas()

returns required ancillas

required_ancillas_controlled

BernoulliDistribution.required_ancillas_controlled()

returns required ancillas controlled

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