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Quantum computing and quantum machine learning for engineers and developers

Record Type:	Electronic resources : Monograph/item
Title/Author:	Quantum computing and quantum machine learning for engineers and developers / by Jesse Van Griensven Thé, Roydon Andrew Fraser, Jose Rosas-Bustos.
Author:	Van Griensven Thé, Jesse.
other author:	Fraser, Roydon Andrew.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xxxvii, 675 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction to Quantum Computing -- Fundamentals of Quantum Mechanics -- Quantum Algorithms -- Quantum Computing Hardware -- Introduction to Quantum AI -- Quantum Data Structures and Encoding -- Quantum Neural Networks -- Quantum Optimization Techniques -- Quantum Communication and Cryptography -- Tools and Platforms for Quantum Computing -- Industry Applications of Quantum Computing -- Future Trends in Quantum AI and Engineering.
Contained By:	Springer Nature eBook
Subject:	Quantum computing. -
Online resource:	https://doi.org/10.1007/978-3-031-98245-3
ISBN:	9783031982453

Quantum computing and quantum machine learning for engineers and developers
Van Griensven Thé, Jesse.

Quantum computing and quantum machine learning for engineers and developers [electronic resource] /by Jesse Van Griensven Thé, Roydon Andrew Fraser, Jose Rosas-Bustos. - Cham :Springer Nature Switzerland :2025. - xxxvii, 675 p. :ill., digital ;24 cm.

Introduction to Quantum Computing -- Fundamentals of Quantum Mechanics -- Quantum Algorithms -- Quantum Computing Hardware -- Introduction to Quantum AI -- Quantum Data Structures and Encoding -- Quantum Neural Networks -- Quantum Optimization Techniques -- Quantum Communication and Cryptography -- Tools and Platforms for Quantum Computing -- Industry Applications of Quantum Computing -- Future Trends in Quantum AI and Engineering.

This book guides readers from the foundations of quantum mechanics through advanced quantum algorithms (such as Shor's and Grover's) and state-of-the-art machine learning methods. By illustrating how these concepts apply to everyday engineering challenges, ranging from complex optimization and cryptography to high-fidelity simulations, the authors equip readers with the tools they need to develop and deploy quantum-based solutions. Incorporating practical case studies, industry-standard platforms, and tested pedagogical approaches, this resource speaks to both academic researchers and industry professionals, enabling them to seamlessly integrate quantum technologies into their projects and workflows. Draws on content rigorously tested at the PhD level, ensuring both scholarly depth and practical relevance; Features comprehensive coverage of quantum algorithms and machine learning methods tailored to engineering problems; Provides a hands-on, practice-oriented framework using industry-standard platforms: Qiskit, Cirq, and PennyLane.

ISBN: 9783031982453

Standard No.: 10.1007/978-3-031-98245-3doiSubjects--Topical Terms:

2115803
Quantum computing.

LC Class. No.: QA76.889 / .V36 2025

Dewey Class. No.: 006.3843

Quantum computing and quantum machine learning for engineers and developers
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300 $a xxxvii, 675 p. : $b ill., digital ; $c 24 cm.
505 0 $a Introduction to Quantum Computing -- Fundamentals of Quantum Mechanics -- Quantum Algorithms -- Quantum Computing Hardware -- Introduction to Quantum AI -- Quantum Data Structures and Encoding -- Quantum Neural Networks -- Quantum Optimization Techniques -- Quantum Communication and Cryptography -- Tools and Platforms for Quantum Computing -- Industry Applications of Quantum Computing -- Future Trends in Quantum AI and Engineering.
520 $a This book guides readers from the foundations of quantum mechanics through advanced quantum algorithms (such as Shor's and Grover's) and state-of-the-art machine learning methods. By illustrating how these concepts apply to everyday engineering challenges, ranging from complex optimization and cryptography to high-fidelity simulations, the authors equip readers with the tools they need to develop and deploy quantum-based solutions. Incorporating practical case studies, industry-standard platforms, and tested pedagogical approaches, this resource speaks to both academic researchers and industry professionals, enabling them to seamlessly integrate quantum technologies into their projects and workflows. Draws on content rigorously tested at the PhD level, ensuring both scholarly depth and practical relevance; Features comprehensive coverage of quantum algorithms and machine learning methods tailored to engineering problems; Provides a hands-on, practice-oriented framework using industry-standard platforms: Qiskit, Cirq, and PennyLane.
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650 2 4 $a Cryptology. $3 3382308
650 2 4 $a Electronic Circuits and Systems. $3 3538814
650 2 4 $a Algorithms. $3 536374
700 1 $a Fraser, Roydon Andrew. $3 3791606
700 1 $a Rosas-Bustos, Jose. $3 3791607
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