Types
Qadence Types
AlgoHEvo
Bases: StrEnum
Hamiltonian Evolution algorithms that can be used by the backend.
EIG = 'EIG'
class-attribute
instance-attribute
Using Hamiltonian diagonalization.
EXP = 'EXP'
class-attribute
instance-attribute
Using torch.matrix_exp on the generator matrix.
RK4 = 'RK4'
class-attribute
instance-attribute
4th order Runge-Kutta approximation.
BasisSet
Bases: StrEnum
Basis set for feature maps.
CHEBYSHEV = 'Chebyshev'
class-attribute
instance-attribute
Chebyshev polynomials of the first kind.
FOURIER = 'Fourier'
class-attribute
instance-attribute
Fourier basis set.
DeviceType
Bases: StrEnum
Supported types of devices for Pulser backend.
IDEALIZED = 'IdealDevice'
class-attribute
instance-attribute
Idealized device, least realistic.
REALISTIC = 'RealisticDevice'
class-attribute
instance-attribute
Device with realistic specs.
Endianness
Bases: StrEnum
The endianness convention to use.
BIG = 'Big'
class-attribute
instance-attribute
Use Big endianness.
LITTLE = 'Little'
class-attribute
instance-attribute
Use little endianness.
Interaction
Bases: StrEnum
Interaction types used in.
RydbergDevice.hamiltonian_factory.
NN = 'NN'
class-attribute
instance-attribute
NN-Ising Interaction, N=(I-Z)/2.
XY = 'XY'
class-attribute
instance-attribute
XY Interaction.
XYZ = 'XYZ'
class-attribute
instance-attribute
XYZ Interaction.
ZZ = 'ZZ'
class-attribute
instance-attribute
ZZ-Ising Interaction.
LTSOrder
Bases: StrEnum
Lie-Trotter-Suzuki approximation order.
BASIC = 'BASIC'
class-attribute
instance-attribute
Basic.
ST2 = 'ST2'
class-attribute
instance-attribute
ST2.
ST4 = 'ST4'
class-attribute
instance-attribute
ST4.
OverlapMethod
Bases: StrEnum
Overlap Methods to choose from.
COMPUTE_UNCOMPUTE = 'compute_uncompute'
class-attribute
instance-attribute
Compute-uncompute.
EXACT = 'exact'
class-attribute
instance-attribute
Exact.
HADAMARD_TEST = 'hadamard_test'
class-attribute
instance-attribute
Hadamard-test.
JENSEN_SHANNON = 'jensen_shannon'
class-attribute
instance-attribute
Jensen-shannon.
SWAP_TEST = 'swap_test'
class-attribute
instance-attribute
Swap-test.
ParameterType
Bases: StrEnum
Parameter types available in qadence.
FEATURE = 'Feature'
class-attribute
instance-attribute
FeatureParameters act as input and are not trainable.
FIXED = 'Fixed'
class-attribute
instance-attribute
Fixed/ constant parameters are neither trainable nor act as input.
VARIATIONAL = 'Variational'
class-attribute
instance-attribute
VariationalParameters are trainable.
ResultType
Bases: StrEnum
Available data types for generating certain results.
NUMPY = 'Numpy'
class-attribute
instance-attribute
Numpy Array Type.
STRING = 'String'
class-attribute
instance-attribute
String Type.
TORCH = 'Torch'
class-attribute
instance-attribute
Torch Tensor Type.
ReuploadScaling
Bases: StrEnum
Scaling for data reuploads in feature maps.
CONSTANT = 'Constant'
class-attribute
instance-attribute
Constant scaling.
EXP = 'Exponential'
class-attribute
instance-attribute
Exponentially increasing scaling.
TOWER = 'Tower'
class-attribute
instance-attribute
Linearly increasing scaling.
SerializationFormat
Bases: StrEnum
Available serialization formats for circuits.
JSON = 'JSON'
class-attribute
instance-attribute
The Json format.
PT = 'PT'
class-attribute
instance-attribute
The PT format used by Torch.
StateGeneratorType
Bases: StrEnum
Methods to generate random states.
HAAR_MEASURE_FAST = 'HaarMeasureFast'
class-attribute
instance-attribute
HaarMeasure.
HAAR_MEASURE_SLOW = 'HaarMeasureSlow'
class-attribute
instance-attribute
HaarMeasure non-optimized version.
RANDOM_ROTATIONS = 'RandomRotations'
class-attribute
instance-attribute
Random Rotations.
Strategy
Bases: StrEnum
Computing paradigm.
ANALOG = 'Analog'
class-attribute
instance-attribute
Use the analog paradigm.
BDAQC = 'bDAQC'
class-attribute
instance-attribute
Use the banged digital-analog QC paradigm.
DIGITAL = 'Digital'
class-attribute
instance-attribute
Use the digital paradigm.
SDAQC = 'sDAQC'
class-attribute
instance-attribute
Use the step-wise digital-analog QC paradigm.
TensorType
Bases: StrEnum
Tensor Types for converting blocks to tensors.
DENSE = 'Dense'
class-attribute
instance-attribute
Convert a block to a dense tensor.
SPARSE = 'Sparse'
class-attribute
instance-attribute
Convert a observable block to a sparse tensor.
SPARSEDIAGONAL = 'SparseDiagonal'
class-attribute
instance-attribute
Convert a diagonal observable block to a sparse diagonal if possible.