QN-SPSA for hybrid models

PennyLane Help
1

Hi,

I am working on developing a VQC-based quantum PINN for solving diffusion problems.

In my model, the role of the quantum circuit is to predict a value u, which is then used as part of a classical loss function. I am using the expectation value of a PauliZ observable as the output of the circuit, and integrate it via a TorchLayer.

I have tried optimizing my model via ADAM and LBFGS, but I think it keeps running into barren plateaus and gets stuck in local minima. I wanted to try to incorporate QN-SPSA for optimization to see if it improves my results, however, I am not sure how to do this, since the documentation ( qml.QNSPSAOptimizer — PennyLane 0.41.1 documentation) only mentions using the output of a qnode as the loss function.

I am not sure if my question is ill-posed and using a QN-SPSA (or QNGD) is even possible with a classical loss function.

I would greatly appreciate any help on this!

Thank you,
Klim

2

Hi @Klim
Welcome to the forum!
Unfortunately, we experienced a high volume of questions at the end of the day today and I couldn’t get to this one on time.
I will try to help you next week since I am off tomorrow.

Thanks for understanding.

3

Hi!
I will ask around about the QNSPSA optimizer. But it seems to be the case that it is designed to be used with a qnode as the loss function, see this demo for reference and more information.
Could the qml.SPSAOptimizer be useful in your situation?

Thanks for your question.

4

Hi Daniela,

I would really appreciate if you could ask around, thank you!

I haven’t used simple SPSA, as I wanted to try to incorporate quantum gradients somehow, but thank you for the suggestion.

5

Hi, just to confirm our initial suspicion. Yes, qml.SPSAOptimizer is designed to be used with the output of a QNode as the loss function.
You could try other things, but it is not intended to work with anything else apart from a QNode output.

Thanks for your question!