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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

6.5 Randomness

Many programming languages have functions that return pseudo-random numbers. The prefix “pseudo” is there because they are not genuinely random numbers but, nevertheless, they do well on statistical measurements of how well-distributed the results are. number$random

Given four possible events, E0, E1, E2, and E3, with associated probabilities p0, p1, p2, and p3, how might we use random numbers to simulate these events happening with

Displayed math

The probabilities add up to 1.0, as expected. random programming language$Python

In Python, the random() function returns a random real number r such that 0.0 ≤ r < 1.0. We determine that one of the E0, E1, E2, and E3, events occurred based on the value of r computed. random()`function-name random`module-name

If you are not using Python, use whatever similar function is available in your programming language and environment.

The general scheme is to run the following...

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