RandomLayer

Module: pennylane.templates.layers

RandomLayer(weights, wires, ratio_imprim=0.3, imprimitive=<class 'pennylane.ops.qubit.CNOT'>, rotations=None, seed=42)

A layer of randomly chosen single qubit rotations and 2-qubit entangling gates, acting on randomly chosen qubits.

The number \(k\) of single qubit rotations is inferred from the first dimension of weights.

This is an example of two 4-qubit random layers with four Pauli-y/Pauli-z rotations \(R_y, R_z\), controlled-Z gates as imprimitives, as well as ratio_imprim=0.3:

Note

Using the default seed (or any other fixed integer seed) generates one and the same circuit in every quantum node. To generate different circuit architectures, either use a different random seed, or use seed=None together with the cache=False option when creating a quantum node.

Warning

If you use a random number generator anywhere inside the quantum function without the cache=False option, a new random circuit architecture will be created every time the quantum node is evaluated.

Parameters:

• weights (array[float]) – array of weights of shape (k,)
• wires (Sequence[int]) – sequence of qubit indices that the template acts on

Keyword Arguments:  

• ratio_imprim (float) – value between 0 and 1 that determines the ratio of imprimitive to rotation gates
• imprimitive (pennylane.ops.Operation) – two-qubit gate to use, defaults to CNOT
• rotations (list[pennylane.ops.Operation]) – List of Pauli-X, Pauli-Y and/or Pauli-Z gates. The frequency determines how often a particular rotation type is used. Defaults to the use of all three rotations with equal frequency.
• seed (int) – seed to generate random architecture