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Dancing with Qubits - Second Edition

You're reading from  Dancing with Qubits - Second Edition

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781837636754
Pages 684 pages
Edition 2nd Edition
Languages
Author (1):
Robert S. Sutor Robert S. Sutor
Profile icon Robert S. Sutor

Table of Contents (26) Chapters

Preface I Foundations
Why Quantum Computing They’re Not Old, They’re Classics More Numbers Than You Can Imagine Planes and Circles and Spheres, Oh My Dimensions 6 What Do You Mean “Probably”? II Quantum Computing
One Qubit Two Qubits, Three Wiring Up the Circuits From Circuits to Algorithms Getting Physical III Advanced Topics
Considering NISQ Algorithms Introduction to Quantum Machine Learning Questions about the Future Afterword
A Quick Reference B Notices C Production Notes Other Books You May Enjoy
References
Index
Appendices

13.2 Methods for encoding data

If classical computers use bits 0 and 1, but quantum computers use qubits represented as

Displayed math

for complex a and b, where |a|2 + |b|2 = 1, how do we efficiently map classical data into a multi-qubit quantum representation? We must quantum encode classical data so a quantum computer can use it.

In some instances, it may make sense to encode 0 ↦ |0⟩ and 1 ↦ |1⟩, but this would not be practical if our application involves the huge amount of information typically used in machine learning, for example. In this section, we look at several techniques for quantum-encoding classical data. There is a trade-off between being efficient with time spent encoding and decoding versus the number of qubits needed to store the information.

Suppose we have a real n-dimensional vector x. We want to represent x in an N-qubit state |ψ with Nn. We do this via an encoding circuit or unitary operator...

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