Quantum Artificial Intelligence with Qiskit

This project aims at teaching you the fundamentals of Quantum Artificial Intelligence with Qiskit. It contains the example code of my CRC Press/Taylor & Francis book, Quantum Artificial Intelligence, Andreas Wichert, 2024

http://web.tecnico.ulisboa.pt/andreas.wichert/

Qiskit is an open-source software development kit (SDK) for working with quantum computers at the level of circuits and algorithms, IBM Quantum, https://quantum-computing.ibm.com/.

You can find installation instruction for qiskit at the site: https://qiskit.org/documentation/getting_started.html

For Qiskit version 1.x go to the directory

https://github.com/andrzejwichert/qai_1

For Qiskit version 2.x go to the directory

https://github.com/andrzejwichert/qai2

For better dependency management, consider using a virtual environments using conda

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Qiskit 0.x versions (old)

Use pip to install the desired version. Replace X.Y.Z with the version number you need:

pip install qiskit==X.Y.Z

For exmpla to instal qiskit 0.46:

pip install qiskit==0.46

The notebooks use some basic commands and should be compatible with different qiskit 0.x versions, expect the notebook 23_HybridApproaches-VariationalClassification and 17_QuantumKernels.

The symbol (+) after the name, like “17_QuantumKernels(+).ipynb” indicates that the algorithm was ported to the newest qiskit version (now qiskit 0.45.0 and 0.46.0 with warnings).

i) Instead of .bind_parameters() .assign_parameters() is used, see

17_QuantumKernels(+), 23_HybridApproaches-VariationalClassification(+)

ii) Instead of qiskit.algorithms qiskit_algorithms is used,see

23_HybridApproaches-VariationalClassification(+)

The symbol (-) after the name, like “23_HybridApproaches-VariationalClassification(-).ipynb” indicates that the algorithm uses older qiskit version then in the book.

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If you have any questions, pls email me andreas.wichert@tecnico.ulisboa.pt