Quantum Computing and Quantum Machine Learning for Engineers and Developers
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 crypt...
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| Main Authors: | , , |
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| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | inglés |
| Publicado: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edición: | 1st ed. 2025. |
| Subjects: | |
| Acceso en liña: | https://doi.org/10.1007/978-3-031-98245-3 |
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| 245 | 1 | 0 | |a Quantum Computing and Quantum Machine Learning for Engineers and Developers |h [electronic resource] / |c by Jesse Van Griensven Thé, Roydon Andrew Fraser, Jose Rosas-Bustos. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2025. | |
| 300 | |a 1 online resource (XXXVII, 675 p. 73 illus.). |b 67 illus. in color. | ||
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| 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. | ||
| 532 | 8 | |a Accessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Quantum computers. | |
| 650 | 0 | |a Cryptography. | |
| 650 | 0 | |a Data encryption (Computer science). | |
| 650 | 0 | |a Electronic circuits. | |
| 650 | 0 | |a Algorithms. | |
| 650 | 1 | 4 | |a Machine Learning. |
| 650 | 2 | 4 | |a Quantum Computing. |
| 650 | 2 | 4 | |a Cryptology. |
| 650 | 2 | 4 | |a Electronic Circuits and Systems. |
| 650 | 2 | 4 | |a Algorithms. |
| 700 | 1 | |a Fraser, Roydon Andrew. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Rosas-Bustos, Jose. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-98245-3 |
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| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||
| 950 | |a Focus Bundle Artificial Intelligence (SpringerNature-85418) | ||