Integrated quantum bayesian inference

[proeseler]

Summary

This pull request introduces the QBayesian class to the Qiskit Machine Learning library. The class implements the Quantum Bayesian Inference algorithm, providing a quantum-based approach to infer probabilities in Bayesian networks. This enhancement aligns with the ongoing efforts to expand the library's capabilities in quantum machine learning algorithms. The algorithm is based on the paper from Low, Guang Hao, Theodore J. Yoder, and Isaac L. Chuang. "Quantum inference on Bayesian networks", Physical Review A 89.6 (2014): 062315.

Details and comments

• Added QBayesian class in qiskit_machine_learning/algorithms/inference.
• Included unit tests for the new class in tests/algorithms/inference.
• Updated documentation to reflect the addition of QBayesian and included a tutorial in docs.

✅ I have added the tests to cover my changes.
✅ I have updated the documentation accordingly.
✅ I have read the CONTRIBUTING document.

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[declanmillar]

Thanks very much for introducing this exciting feature! I've made a few surface-level suggestions, but I need to go through the method and tutorial in more detail to check my understanding of the implementation.

[edoaltamura]

We'll need to re-run CI tests with the most up-to-date dev branch just before merging. Looking forward to having Bayesian methods in the codebase!

[proeseler]

I'm not even sure I can, but should I merge it or do you?

[edoaltamura]

I would be happy to go ahead, but I would like to hear the opinions of @woodsp-ibm and @OkuyanBoga. Do you think this is a good time to merge?

[woodsp-ibm]

Do you think this is a good time to merge?

It seems fine to me given the expectation that this feature will be in the next main release.

[OkuyanBoga]

Thank you all, I merged it after the approvals.