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Quantum Computing in Practice with Qiskit® and IBM Quantum Experience®

You're reading from   Quantum Computing in Practice with Qiskit® and IBM Quantum Experience® Practical recipes for quantum computer coding at the gate and algorithm level with Python

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781838828448
Length 408 pages
Edition 1st Edition
Languages
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Author (1):
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Hassi Norlen Hassi Norlen
Author Profile Icon Hassi Norlen
Hassi Norlen
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Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Preparing Your Environment 2. Chapter 2: Quantum Computing and Qubits with Python FREE CHAPTER 3. Chapter 3: IBM Quantum Experience® – Quantum Drag and Drop 4. Chapter 4: Starting at the Ground Level with Terra 5. Chapter 5: Touring the IBM Quantum® Hardware with Qiskit® 6. Chapter 6: Understanding the Qiskit® Gate Library 7. Chapter 7: Simulating Quantum Computers with Aer 8. Chapter 8: Cleaning Up Your Quantum Act with Ignis 9. Chapter 9: Grover's Search Algorithm 10. Chapter 10: Getting to Know Algorithms with Aqua 11. Other Books You May Enjoy

Adding noise profiles of IBM Quantum® backends to local simulators

In this recipe, we find the noise data for the IBM Quantum® backends to build a noise profile that we can then add to our simulator when we run it. This will make the simulator behave like a real NISQ backend.

Getting ready

The sample code for this recipe can be found here: https://github.com/PacktPublishing/Quantum-Computing-in-Practice-with-Qiskit-and-IBM-Quantum-Experience/blob/master/Chapter07/ch7_r3_noise.py.

How to do it...

Let's look at the following code:

  1. Get a list of the available backends and select one to simulate.

    We will get the noise profile of one of the IBM Quantum® backends and use it with our simulators. First, we use the select_backend() function to list the backends and make the selection:

    def select_backend():
        # Get all available and operational backends.
        available_backends = provider.backends(filters=lambda ...
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