A notebook-first introduction to quantum computing using Qiskit.
Resources open inside this site. Guides, papers, figures, notebooks, and source files are organized around the project’s story.
Welcome to the "Learn Quantum Computing with Qiskit" repository! This repository aims to provide a comprehensive learning resource for quantum computing using the Qiskit…
Qiskit is an open-source framework developed by IBM for programming quantum computers. It provides a rich set of tools, libraries, and resources to facilitate quantum computation research and education. With Qiskit, you can learn, simulate, and execute quantum circuits on real quantum hardware devices or simulators.
This is a comprehensive guide for setting up your environment on your personal computer for working with Qiskit Textbook. This will help you reproduce the results as you see them on the textbook website. The Qiskit Textbook is written in Jupyter Notebooks.
Learn about the software used to write the Qiskit (Python and Jupyter Notebooks), and set up your environment to reproduce the experiments.
If you think quantum mechanics sounds challenging, you’re not alone. Our intuitions come from day-to-day experiences, and so are better at understanding the behavior of balls and bananas than atoms or…
This chapter introduces the computing concepts that we'll explore in later chapters, then introduces basic quantum concepts.
We've seen some interesting effects with isolated qubits and single qubit gates, but the true power of quantum computing comes from interactions between qubits. In this section we will introduce multiple qubit gates and explore the interesting behaviours of multi-qubit systems.
With the basics down, this chapter explores the consequences of these new quantum effects, and sets us up with tools to understand quantum algorithms.
So far, we've seen various quantum gates and operations, and we've explored some interesting properties of these gates. Each of these pages shows how we can combine quantum operations into a quantum algorithm that outperforms their classical counterpart. As a bonus, some of these algorithms are actually useful too!
In this chapter, we use quantum effects to build powerful algorithms, starting from simple proof-of-concept algorithms, through to Shor's famous factoring algorithm (and beyond).
In this chapter, we get a level closer to the real quantum machines. Learn about the physics of these devices, and how to program them at the level of microwave pulses.
If algorithms are the solution, then what is the problem? In this chapter, we look at how we can take general algorithms and apply them to more specific situations.
All circuit-based quantum devices share some similar characteristics and challenges. In this chapter, we explore how quantum circuits perform on modern quantum computers, and ways to improve performance.
To get started, make sure you have the following prerequisites:
- Python 3: Ensure you have Python 3 installed on your system. - Qiskit: Install the Qiskit framework by following the instructions provided in the official Qiskit documentation.
Once you have the prerequisites ready, clone this repository to your local machine:
You can then access the notebooks through your browser and start learning quantum computing with Qiskit!
Contributions to this repository are welcome. If you have any suggestions, bug fixes, or additional content to contribute, please open an issue or submit a pull request. Let's work together to make this learning resource even better!
The content of this repository is licensed under the [MIT License](LICENSE). Feel free to use, modify, and distribute the code and notebooks for educational purposes.
Happy learning and exploring the fascinating world of quantum computing with Qiskit!
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