Encodings

Amplitude Encoding

class AmplitudeEncoding(n_features=2)[source]

Amplitude Encoding map

Creates a generic Encoding Map for classical data of size n_features

construct_circuit(x)[source]

Constructs circuit for amplitude encoding

Parameters: x – 1D classical data vector to be encoded must satisfy len(x) == num_features
Return type: QuantumCircuit

state_vector(x)[source]

The encoding of a state via amplitude encoding operates as follows: given a quantum state \(\psi\), it processes the data such that

class AngleEncoding(n_features=2, rotation='Y', scaling=1.5707963267948966)[source]

Angle Encoding algorithm. Assumes data is feature-normalized.

Parameters

rotation – the direction admitted values: X, Y, Z
scaling – scaling factor for normalized input data. The default scaling \(\pi/2\) does not induce a relative phase difference.

construct_circuit(x)[source]

Parameters: x (np.array) – The input data to encode
Return type: QuantumCircuit
Returns: The circuit that encodes x. Assumes data is feature-normalized. Assumes every element in x is in [0, 1]

state_vector(x)[source]

The encoding of a state via angle encoding, operating a rotation around the rotation axis.

class BasisEncoding(n_features=2)[source]

Bases: qlearnkit.encodings.encoding_map.EncodingMap

Initializes Basis Encoding Map

construct_circuit(x)[source]

Retrieves the quantum circuit encoding via Basis Encoding

Note

All data values must be either 1s or 0s

class EncodingMap(n_features=2)[source]

Bases: abc.ABC

Abstract Base class for qlearnkit encoding maps

Creates a generic Encoding Map for classical data of size n_features

abstract construct_circuit(x)[source]

construct and return quantum circuit encoding data