UniformDistribution
class UniformDistribution(num_target_qubits, low=0, high=1)
The Univariate Uniform Distribution.
Uniform distribution is defined by the number of qubits that should be used to represent the distribution, as well as the lower bound and upper bound of the considered interval.
Parameters
- num_target_qubits (
int) – Number of qubits it acts on, has a minimum value of 1. - 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)
Attributes
high
returns high
low
returns low
num_target_qubits
Returns the number of target qubits
num_values
returns number of values
probabilities
returns probabilities
values
returns values
Methods
build
UniformDistribution.build(qc, q, q_ancillas=None, params=None)
build_controlled
UniformDistribution.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
UniformDistribution.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
UniformDistribution.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
UniformDistribution.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
UniformDistribution.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
UniformDistribution.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
UniformDistribution.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
UniformDistribution.get_num_qubits()
returns number of qubits
get_num_qubits_controlled
UniformDistribution.get_num_qubits_controlled()
returns number of qubits controlled
pdf_to_probabilities
static UniformDistribution.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
UniformDistribution.required_ancillas()
returns required ancillas
required_ancillas_controlled
UniformDistribution.required_ancillas_controlled()
returns required ancillas controlled