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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

6.2 More formally

In the last section, there were initially four different possible outcomes: the four kinds of cookies that could pop out of our machine. In this situation, our sample space is the collection sample space

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We also say that these four are the values of a random variable. Random variables usually have names such as X and Y. probability$random variable

A probability distribution assigns a probability to each possible outcome, which are the values of the random variable. The probability distribution for the balanced case is probability$distribution

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When the probabilities are all equal, as in this case, we have a uniform distribution. probability$uniform distribution

If our sample space is finite or, at most, countably infinite, we say it is discrete. A set is countably infinite if it can be put in one-to-one correspondence with Z. sample space$discrete

The sample space is continuous if it can be put in correspondence...

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