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Learn Quantum Computing with Python and IBM Quantum Experience

You're reading from   Learn Quantum Computing with Python and IBM Quantum Experience A hands-on introduction to quantum computing and writing your own quantum programs with Python

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Product type Paperback
Published in Sep 2020
Publisher Packt
ISBN-13 9781838981006
Length 510 pages
Edition 1st Edition
Languages
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Author (1):
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Robert Loredo Robert Loredo
Author Profile Icon Robert Loredo
Robert Loredo
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Tour of the IBM Quantum Experience (QX)
2. Chapter 1: Exploring the IBM Quantum Experience FREE CHAPTER 3. Chapter 2: Circuit Composer – Creating a Quantum Circuit 4. Chapter 3: Creating Quantum Circuits using Quantum Lab Notebooks 5. Section 2: Basics of Quantum Computing
6. Chapter 4: Understanding Basic Quantum Computing Principles 7. Chapter 5: Understanding the Quantum Bit (Qubit) 8. Chapter 6: Understanding Quantum Logic Gates 9. Section 3: Algorithms, Noise, and Other Strange Things in Quantum World
10. Chapter 7: Introducing Qiskit and its Elements 11. Chapter 8: Programming with Qiskit Terra 12. Chapter 9: Monitoring and Optimizing Quantum Circuits 13. Chapter 10: Executing Circuits Using Qiskit Aer 14. Chapter 11: Mitigating Quantum Errors Using Ignis 15. Chapter 12: Learning about Qiskit Aqua 16. Chapter 13: Understanding Quantum Algorithms 17. Chapter 14: Applying Quantum Algorithms 18. Assessments 19. Other Books You May Enjoy Appendix A: Resources

Mitigating readout errors

Ignis has measurement filters that can be used to mitigate various types of errors, such as measurements and tensors.

The measurement calibration is what we will use to mitigate measurement errors in this section. The process begins by first generating a list of circuits, where each circuit represents each of all the possible states of the qubits specified, then executing the circuits on an ideal simulator, the results of which we will then pass into a measurement filter. The measurement filter will then be used to mitigate the measurement errors. In the following example, we will first run the circuits on a simulator without any noise models. Then, we will create a noise model that will be applied to all the qubits of the simulator. Then we will execute the circuits on the noisy backend device, where we will then apply the measurement filter to mitigate the errors as best we can. Finally, we will view the results of the measurement filter and compare them...

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