squlearn.encoding_circuit.KyriienkoEncodingCircuit

class squlearn.encoding_circuit.KyriienkoEncodingCircuit(num_qubits: int, num_features: int = 1, encoding_style: str = 'chebyshev_tower', variational_arrangement: str = 'HEA', num_encoding_layers: int = 1, num_variational_layers: int = 1, rotation_gate: str = 'ry', block_width: int = 2, block_depth: int = 1)

Collection of encoding circuits introduced by Kyriienko et al. in reference [1].

The following circuits are implemented:

  • chebyshev_tower encoding (Eq. 15),

  • chebyshev_sparse encoding (Eq. 14)

  • chebyshev_product encoding (Eq. 5).

Each encoding circuit is followed by a variational circuit as defined in reference [1], RZ-RX-RZ layers followed by entangling layers. Two arrangements are possible:

  • HEA: Hardware Efficient Ansatz, with consecutive entangling layers (See Figure 5a or Section IIIB in [1])

  • ABA: Alternating Block Ansatz with consecutive shifted entangling layers in each block (See Figure 5b or Section IIIB in [1])

Example: 4 qubits, a 2 dimensional feature vector, 1 encoding layer, 2 variational layers, variational arrangement ABA and Chebyshev tower encoding:

(Source code, png, hires.png, pdf)

../../_images/squlearn-encoding_circuit-KyriienkoEncodingCircuit-1.png
Parameters:

  • num_qubits (int) – Number of qubits of the encoding circuit

  • encoding_style (str) – Style of the encoding. Options are 'chebyshev_tower' (default), 'chebyshev_sparse' and 'chebyshev_product' (see reference [1], Equation 15, 14 and 5 respectively)

  • variational_arrangement (str) – Arrangement of the variational layers. Options are 'HEA' (default) and 'ABA' (see reference [1], section IIIB)

  • num_encoding_layers (int) – Number of encoding layers (default: 1)

  • num_variational_layers (int) – Number of variational layers (default: 1)

  • rotation_gate (str) – Rotation gate to use. Either 'rx', 'ry' or 'rz' (default: 'ry' as in reference [1])

  • num_features (int) – Dimension of the feature vector (default: 1)

  • block_width (int) – Only necessary for arrangement 'ABA'. Width (vertical) of each blocks for the ABA arrangement (default: 2), also refered as Nb in the paper. Must be a divisor of the number of qubits

  • block_depth (int) – Only necessary for arrangement 'ABA'. Depth (horizontal) of each blocks for the ABA arrangement (default: 1), also refered as b in the paper.

References

[1]: O. Kyriienko et al., “Solving nonlinear differential equations with differentiable quantum circuits”, arXiv:2011.10395 (2021).

draw(output: str = None, feature_label: str = 'x', parameter_label: str = 'p', decompose: bool = False, **kwargs) → None

Draws the encoding circuit circuit using the QuantumCircuit.draw() function.

Parameters:

  • feature_label (str) – Label for the feature vector (default:”x”).

  • parameter_label (str) – Label for the parameter vector (default:”p”).

  • decompose (bool) – If True, the circuit is decomposed before printing (default: False).

  • kwargs – Additional arguments from Qiskit’s QuantumCircuit.draw() function.

Returns:

Returns the circuit in qiskit QuantumCircuit.draw() format

generate_initial_parameters(seed: int | None = None) → ndarray

Generates random parameters for the encoding circuit

Parameters:

seed (Union[int,None]) – Seed for the random number generator (default: None)

Returns:

The randomly generated parameters

get_circuit(features: ParameterVector | ndarray, parameters: ParameterVector | ndarray) → QuantumCircuit

Generates and returns the circuit of the Kyriienko encoding circuit

Parameters:

  • features (Union[ParameterVector, np.ndarray]) – The features to encode

  • parameters (Union[ParameterVector, np.ndarray]) – The parameters of the encoding circuit

Returns:

The encoding circuit

Return type:

QuantumCircuit

get_params(deep: bool = True) → dict

Returns hyper-parameters and their values of the Kyriienko encoding circuit

Parameters:

deep (bool) – If True, also the parameters for contained objects are returned (default=True).

Returns:

Dictionary with hyper-parameters and values.

set_params(**params) → EncodingCircuitBase

Sets value of the encoding circuit hyper-parameters.

Parameters:

params – Hyper-parameters and their values, e.g. num_qubits=2.