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Dancing with Qubits

You're reading from   Dancing with Qubits From qubits to algorithms, embark on the quantum computing journey shaping our future

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781837636754
Length 684 pages
Edition 2nd Edition
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Author (1):
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Robert S. Sutor Robert S. Sutor
Author Profile Icon Robert S. Sutor
Robert S. Sutor
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Table of Contents (26) Chapters Close

Preface I Foundations
Why Quantum Computing FREE CHAPTER 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

6.7 Hellinger distance

This section examines how we can measure the similarity between two comparable collections using the concept of Hellinger distance. The idea is that if the two collections are “close to each other distance-wise,” they are similar. similarity$Hellinger distance

Consider the game of pool, played with a cue and solid and striped balls on a table. Suppose I have a large box and place one hundred yellow pool balls, one hundred red pool balls, one hundred blue pool balls, and one hundred purple pool balls in the box. I mix the balls thoroughly, so if I reach in and take out a ball, I have the same probability of getting one color as any other. That is, I have a uniform distribution of the balls.

I reach into the box and remove one hundred balls. I record the colors and the count of each:

Displayed math

I put the balls back in the box, stir them up well, and then you remove one hundred balls. Oddly, you pull out balls with the same...

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