LinearAmplitudeFunction
class qiskit.circuit.library.LinearAmplitudeFunction(num_state_qubits, slope, offset, domain, image, rescaling_factor=1, breakpoints=None, name='F')
Bases: QuantumCircuit
A circuit implementing a (piecewise) linear function on qubit amplitudes.
An amplitude function of a function is a mapping
for a function , where is a qubit state.
This circuit implements for piecewise linear functions . In this case, the mapping can be approximately implemented using a Taylor expansion and linearly controlled Pauli-Y rotations, see [1, 2] for more detail. This approximation uses a rescaling_factor
to determine the accuracy of the Taylor expansion.
In general, the function of interest is defined from some interval , the domain
to , the image
, instead of to . Using an affine transformation we can rescale to :
with
If is a piecewise linear function on intervals with slopes and offsets it can be written as
where is an indication function that is 1 if the argument is in the interval and otherwise 0. The breakpoints can be specified by the breakpoints
argument.
References
[1]: Woerner, S., & Egger, D. J. (2018).
Quantum Risk Analysis. arXiv:1806.06893
[2]: Gacon, J., Zoufal, C., & Woerner, S. (2020).
Quantum-Enhanced Simulation-Based Optimization. arXiv:2005.10780
Parameters
- num_state_qubits (int) – The number of qubits used to encode the variable .
- slope (float |list[float]) – The slope of the linear function. Can be a list of slopes if it is a piecewise linear function.
- offset (float |list[float]) – The offset of the linear function. Can be a list of offsets if it is a piecewise linear function.
- domain (tuple[float, float]) – The domain of the function as tuple .
- image (tuple[float, float]) – The image of the function as tuple .
- rescaling_factor (float) – The rescaling factor to adjust the accuracy in the Taylor approximation.
- breakpoints (list[float] | None) – The breakpoints if the function is piecewise linear. If None, the function is not piecewise.
- name (str) – Name of the circuit.
Attributes
ancillas
A list of AncillaQubit
s in the order that they were added. You should not mutate this.
calibrations
Return calibration dictionary.
The custom pulse definition of a given gate is of the form {'gate_name': {(qubits, params): schedule}}
The property qiskit.circuit.quantumcircuit.QuantumCircuit.calibrations
is deprecated as of Qiskit 1.3. It will be removed in Qiskit 2.0. The entire Qiskit Pulse package is being deprecated and will be moved to the Qiskit Dynamics repository: https://github.com/qiskit-community/qiskit-dynamics. Note that once removed, qiskit.circuit.quantumcircuit.QuantumCircuit.calibrations
will have no alternative in Qiskit.
clbits
A list of Clbit
s in the order that they were added. You should not mutate this.
data
The circuit data (instructions and context).
Returns
a list-like object containing the CircuitInstruction
s for each instruction.
Return type
QuantumCircuitData
duration
The total duration of the circuit, set by a scheduling transpiler pass. Its unit is specified by unit
.
The property qiskit.circuit.quantumcircuit.QuantumCircuit.duration
is deprecated as of Qiskit 1.3.0. It will be removed in Qiskit 2.0.0.
global_phase
The global phase of the current circuit scope in radians.
instances
Default value: 184
layout
Return any associated layout information about the circuit
This attribute contains an optional TranspileLayout
object. This is typically set on the output from transpile()
or PassManager.run()
to retain information about the permutations caused on the input circuit by transpilation.
There are two types of permutations caused by the transpile()
function, an initial layout which permutes the qubits based on the selected physical qubits on the Target
, and a final layout which is an output permutation caused by SwapGate
s inserted during routing.
metadata
Arbitrary user-defined metadata for the circuit.
Qiskit will not examine the content of this mapping, but it will pass it through the transpiler and reattach it to the output, so you can track your own metadata.
num_ancillas
Return the number of ancilla qubits.
num_captured_vars
The number of real-time classical variables in the circuit marked as captured from an enclosing scope.
This is the length of the iter_captured_vars()
iterable. If this is non-zero, num_input_vars
must be zero.
num_clbits
Return number of classical bits.
num_declared_vars
The number of real-time classical variables in the circuit that are declared by this circuit scope, excluding inputs or captures.
This is the length of the iter_declared_vars()
iterable.
num_input_vars
The number of real-time classical variables in the circuit marked as circuit inputs.
This is the length of the iter_input_vars()
iterable. If this is non-zero, num_captured_vars
must be zero.
num_parameters
The number of parameter objects in the circuit.
num_qubits
Return number of qubits.
num_vars
The number of real-time classical variables in the circuit.
This is the length of the iter_vars()
iterable.
op_start_times
Return a list of operation start times.
This attribute is enabled once one of scheduling analysis passes runs on the quantum circuit.
Returns
List of integers representing instruction start times. The index corresponds to the index of instruction in QuantumCircuit.data
.
Raises
AttributeError – When circuit is not scheduled.
parameters
The parameters defined in the circuit.
This attribute returns the Parameter
objects in the circuit sorted alphabetically. Note that parameters instantiated with a ParameterVector
are still sorted numerically.
Examples
The snippet below shows that insertion order of parameters does not matter.
>>> from qiskit.circuit import QuantumCircuit, Parameter
>>> a, b, elephant = Parameter("a"), Parameter("b"), Parameter("elephant")
>>> circuit = QuantumCircuit(1)
>>> circuit.rx(b, 0)
>>> circuit.rz(elephant, 0)
>>> circuit.ry(a, 0)
>>> circuit.parameters # sorted alphabetically!
ParameterView([Parameter(a), Parameter(b), Parameter(elephant)])
Bear in mind that alphabetical sorting might be unintuitive when it comes to numbers. The literal “10” comes before “2” in strict alphabetical sorting.
>>> from qiskit.circuit import QuantumCircuit, Parameter
>>> angles = [Parameter("angle_1"), Parameter("angle_2"), Parameter("angle_10")]
>>> circuit = QuantumCircuit(1)
>>> circuit.u(*angles, 0)
>>> circuit.draw()
┌─────────────────────────────┐
q: ┤ U(angle_1,angle_2,angle_10) ├
└─────────────────────────────┘
>>> circuit.parameters
ParameterView([Parameter(angle_1), Parameter(angle_10), Parameter(angle_2)])
To respect numerical sorting, a ParameterVector
can be used.
>>> from qiskit.circuit import QuantumCircuit, Parameter, ParameterVector
>>> x = ParameterVector("x", 12)
>>> circuit = QuantumCircuit(1)
>>> for x_i in x:
... circuit.rx(x_i, 0)
>>> circuit.parameters
ParameterView([
ParameterVectorElement(x[0]), ParameterVectorElement(x[1]),
ParameterVectorElement(x[2]), ParameterVectorElement(x[3]),
..., ParameterVectorElement(x[11])
])
Returns
The sorted Parameter
objects in the circuit.
prefix
Default value: 'circuit'
qubits
A list of Qubit
s in the order that they were added. You should not mutate this.
unit
The unit that duration
is specified in.
The property qiskit.circuit.quantumcircuit.QuantumCircuit.unit
is deprecated as of Qiskit 1.3.0. It will be removed in Qiskit 2.0.0.
name
Type: str
A human-readable name for the circuit.
qregs
Type: list[QuantumRegister]
A list of the QuantumRegister
s in this circuit. You should not mutate this.
cregs
Type: list[ClassicalRegister]
A list of the ClassicalRegister
s in this circuit. You should not mutate this.
Methods
post_processing
post_processing(scaled_value)
Map the function value of the approximated to .
Parameters
scaled_value (float) – A function value from the Taylor expansion of .
Returns
The scaled_value
mapped back to the domain of , by first inverting the transformation used for the Taylor approximation and then mapping back from to the original domain.
Return type