This is my first message here, then I would like to thank all Xanadu staff for this fantastic library, I am deeply in love with it.
I am fitting a Fano resonance over 20 scattered points I obtained in the lab with SF, I got some good results on fitting with the simulator and I would like to send the code to the photonic backend X8, please can you point me some information about how to measure the outcome? I get an error on the X-gate which is not allowed in the real backend.
Thank you for your kind words about our libraries. Thank you for using them and sharing your love for them!
I think the problem you’re having is related to the data you’re inputting.
I ran the following code and I got no errors. You should check the dimensions in your data to make sure that whatever goes into the Displacement gate is a single float.
import pennylane as qml
from pennylane import numpy as np
dev = qml.device("strawberryfields.tf", wires=1, cutoff_dim=10)
def layer(v):
qml.CVNeuralNetLayers(*v, wires=list(range(num_qubits)))
@qml.qnode(dev)
def quantum_neural_net(var, x):
# Encode input x into quantum state
for i in range(num_qubits):
#qml.Rotation(x, wires=i)
qml.Displacement(x, 0.0, wires=i)
layer(var)
return qml.expval(qml.X(0))
np.random.seed(0)
num_qubits = 1
shapes = qml.CVNeuralNetLayers.shape(n_layers=3, n_wires=num_qubits)
weights = [np.random.random(shape) for shape in shapes]
x = 0.1
quantum_neural_net(weights, x)
Please let me know if this solves your problem, or otherwise please share a minimal version of your code, with an example of your ‘X_data’ after all of the processing that you perform.