Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Learn Quantum Computing with Python and IBM Quantum
  • Toc
  • feedback
Learn Quantum Computing with Python and IBM Quantum

Learn Quantum Computing with Python and IBM Quantum

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

Learn Quantum Computing with Python and IBM Quantum

By: Robert Loredo

Overview of this book

IBM Quantum Lab is a platform that enables developers to learn the basics of quantum computing by allowing them to run experiments on a quantum computing simulator and on several real quantum computers. Updated with new examples and changes to the platform, this edition begins with an introduction to the IBM Quantum dashboard and Quantum Information Science Kit (Qiskit) SDK. You will become well versed with the IBM Quantum Composer interface as well as the IBM Quantum Lab. You will learn the differences between the various available quantum computers and simulators. Along the way, you’ll learn some of the fundamental principles regarding quantum mechanics, quantum circuits, qubits, and the gates that are used to perform operations on qubits. As you build on your knowledge, you’ll understand the functionality of IBM Quantum and the developer-focused resources it offers to address key concerns like noise and decoherence within a quantum system. 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 programs and will have gained a practical understanding of quantum computation that you can apply to your business.
Table of Contents (18 chapters)
close
14
Other Book You May Enjoy
15
Index

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...

bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete