# Qutrit measurements in pennylane model

**URL:** <https://discuss.pennylane.ai/t/qutrit-measurements-in-pennylane-model/3177>\
**Category:** PennyLane Help\
**Created:** [July 11, 2023, 5:53pm UTC](https://discuss.pennylane.ai/t/qutrit-measurements-in-pennylane-model/3177 "2023-07-11T17:53:26Z")\
**Posts on this page:** 4\
**Page:** 1

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**Author:** ![kevinkawchak](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/kevinkawchak/32/1801_2.png) [@kevinkawchak](https://discuss.pennylane.ai/u/kevinkawchak)\
**Post date:** [July 11, 2023, 5:53pm UTC](https://discuss.pennylane.ai/t/qutrit-measurements-in-pennylane-model/3177/1 "2023-07-11T17:53:26Z")

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Assistance regarding implementing qutrit measurements into pennylane model.

```
Expectation values in the Z basis
exp_vals = [qml.expval(qml.PauliZ(position)) for position in range(n_qubits)]
return tuple(exp_vals)

```

Source:

> **[Quantum transfer learning](https://pennylane.ai/qml/demos/tutorial_quantum_transfer_learning/)**
>
> Combine PyTorch and PennyLane to train a hybrid quantum-classical image classifier using transfer learning.

Thank you.

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<div class="post-metadata">

**Author:** ![isaacdevlugt](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/isaacdevlugt/32/1159_2.png) [@isaacdevlugt](https://discuss.pennylane.ai/u/isaacdevlugt)\
**Post date:** [July 11, 2023, 7:30pm UTC](https://discuss.pennylane.ai/t/qutrit-measurements-in-pennylane-model/3177/2 "2023-07-11T19:30:50Z")

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Hey @kevinkawchak! Welcome to the forum 🚀

You can see a complete list of qutrit operations that are available here:

[https://docs.pennylane.ai/en/stable/introduction/operations.html?highlight=qutrits#qutrit-operators](https://docs.pennylane.ai/en/stable/introduction/operations.html?highlight=qutrits#qutrit-operators)

You might also find this demo useful:

> **[Qutrits and quantum algorithms](https://pennylane.ai/qml/demos/tutorial_qutrits_bernstein_vazirani/)**
>
> Learn how to interpret the Bernstein–Vazirani algorithm with qutrits

Let me know if that helps!

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<div class="post-metadata">

**Author:** ![kevinkawchak](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/kevinkawchak/32/1801_2.png) [@kevinkawchak](https://discuss.pennylane.ai/u/kevinkawchak)\
**Post date:** [August 19, 2023, 6:55am UTC](https://discuss.pennylane.ai/t/qutrit-measurements-in-pennylane-model/3177/3 "2023-08-19T06:55:31Z")

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Thank you @isaacdevlugt,  
I was able to run @Guillermo_Alonso’s demo modifying Tshift gates to obtain predictable sets of ternary outputs. What steps would I need to take to implement a user dataset for a classification task, coming from a deep learning port perspective?  
-Kevin

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<div class="post-metadata">

**Author:** ![isaacdevlugt](https://yyz2.discourse-cdn.com/flex012/user_avatar/discuss.pennylane.ai/isaacdevlugt/32/1159_2.png) [@isaacdevlugt](https://discuss.pennylane.ai/u/isaacdevlugt)\
**Post date:** [August 21, 2023, 1:24pm UTC](https://discuss.pennylane.ai/t/qutrit-measurements-in-pennylane-model/3177/4 "2023-08-21T13:24:09Z")

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Nice! The steps you’d need to take to train a qutrit circuit for a classification task will be _extremely_ similar to what’s in our [variational classifier demo](https://pennylane.ai/qml/demos/tutorial_variational_classifier). Let me know if that helps!