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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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14
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15
Index

Understanding quantum and classical system interconnections

In this section, we’ll review how quantum computational systems are integrated with classical systems. As quantum computers do not have ways to store the state of a qubit, there is a dependency on classical systems to provide persistent storage for information that is sent to or received from a quantum computer.

Since most data originates from classical sources, whether they are from data repositories or remote sensors, there is a need to prepare the data to be used in a quantum system. Likewise, the results from the quantum systems need to be returned not in a quantum state but in binary form so that they can be read back to a classical system for any post-processing that’s required.

This hybrid or interconnectivity between classical systems and quantum systems is what we will be reviewing in this section so that you understand how both systems work together to provide you with the most optimal results...

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