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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

13.3 Quantum neural networks

Let’s recall some definitions regarding neural networks from my book Dancing with Python. 211, Section 15.8 neural network quantum$neural network node neuron

Figure 13.3 shows a neural network with three input nodes, four nodes in the hidden layer, and two output nodes. Another name for a node is a neuron. I’ve shown weights w in the network on the connections from the input nodes going to the hidden nodes, and from the hidden nodes to the output nodes. Note how the network sends the value of each node to every node in the next layer.

 Figure 13.3: Neural network with 3 inputs, 4 hidden nodes, and 2 outputs

We compute a value from the input values and weights for each node in the hidden layers. These are real numbers that we may restrict to the binary values 0 and 1. We also have an associated activation function for each node in the hidden layer, determining what value to send to...

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