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Learn Quantum Computing with Python and IBM Quantum

Learn Quantum Computing with Python and IBM Quantum

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

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)
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Index

Simulating Quantum Systems and Noise Models

Qiskit is a provider of high-performance backends that can be used to execute quantum circuits. The various backend simulators available can be used in unique ways where each can provide different information pertaining to your circuit. Qiskit also provides a variety of tools that can be leveraged to construct noise models to simulate various errors that occur on real quantum devices. These tools are very helpful should you need to compare the difference between your results from an ideal simulator and that which replicates the effects of noise from a quantum device.

Both the simulators and tools such as the noise model will help you understand the reasons for some of the effects on your results, as well as provide insights should you later want to mitigate those errors yourself.

The following topics will be covered in this chapter:

  • Understanding the differences between simulators
  • Generating noise models
  • Building...
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