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I have been using PennyLane to run numerical QML simulations but it now seems to only support backprop on pure state simulations. Does anyone familiar with other packages know if there exists one that supports quantum machine learning on mix-states?

Thank you.

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You can use default.mixed on PennyLane for simulating mixed states. However, instead of using backpropagation you can set diff_method="best" when defining your qnode, which in this case will use the parameter-shift rule for differentiation.

EG:

@qml.qnode(dev, diff_method="best")

You can learn more about noisy circuits in PennyLane here or learn about error mitigation with PennyLane here.

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  • $\begingroup$ Hi @Catalina. Thank you for the suggestion. I did try this but it didn't work. What interface did you use? (I tried TensorFlow and autograd). $\endgroup$ Jan 17 at 22:37
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My guess is that you could do something similar to what is outlined in this tutorial, but instead of parametrizing a quantum circuit you could parametrize the mixed states you want. For representing mixed states, you could use QuTiP.

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  • $\begingroup$ Thank you. I'll take a look at QuTIP! $\endgroup$ Jan 11 at 21:45

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