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  • Book Overview & Buying Learn Quantum Computing with Python and IBM Quantum
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Learn Quantum Computing with Python and IBM Quantum

Learn Quantum Computing with Python and IBM Quantum - Second Edition

By : Robert Loredo
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Learn Quantum Computing with Python and IBM Quantum

Learn Quantum Computing with Python and IBM Quantum

By: Robert Loredo

Overview of this book

The IBM Quantum Platform was built to enable developers to learn the basics of quantum computing by providing access to high performant quantum computers and provide documentation and courses to help get up to speed with the latest features in quantum computing. Updated with new examples and changes to the platform, this edition begins with an introduction to the IBM Quantum Platform and the Quantum Information Science Kit (Qiskit) SDK. You will become well versed in the IBM Quantum Composer interface as well as running your quantum circuits on a real quantum computer. Along the way, you’ll learn some of the fundamental principles regarding quantum mechanics, qubits, quantum gates, quantum circuits, and the error mitigation techniques that are used to perform operations on qubits. As you build on your knowledge, you’ll understand the functionality of IBM Qiskit and the developer-focused resources so you can create your own quantum algorithms. You’ll learn how to monitor and optimize your quantum circuits. Lastly, you’ll look at the fundamental quantum algorithms and understand how they can be applied effectively. By the end of this quantum computing book, you'll know how to build quantum algorithms and will have gained a practical understanding of quantum computation that you can apply to your research or business.
Table of Contents (18 chapters)
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14
Other Book You May Enjoy
15
Index
1
Appendix A: Resources

Optimizing and Visualizing Quantum Circuits

In the previous chapter, you learned how to program with Qiskit, using both circuits and pulse schedules. We’ll continue with the topic of circuits in this chapter, specifically some new features that optimize and speed up the end-to-end process by reducing the overhead between the classical and quantum systems during heavy computation cycles.

Luckily, Qiskit provides plenty of features to allow us to do this with ease. Additionally, Qiskit provides a set of classes and features to optimize and enhance the visualizations of your circuits. Learning about these features will help optimize your circuit results and allow you to render the circuits in various styles and representations, such as a directed acyclic graph (DAG).

We will cover the following topics in this chapter:

  • Optimizing circuits using Preset Passmanager
  • Visualizing and enhancing circuit graphs

After reading this chapter, you will be able...

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Learn Quantum Computing with Python and IBM Quantum
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