Quantum Computing Solutions : Solving Real-World Problems Using Quantum Computing and Algorithms / by Bhagvan Kommadi
| Publisher | (Berkeley, CA : Apress : Imprint: Apress) |
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| Year | 2020 |
| Edition | 1st ed. 2020. |
| Authors | *Kommadi, Bhagvan author SpringerLink (Online service) |
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| Links to the text | Location | Volume | Call No. | Barcode No. | Status | Comments | ISBN | Printed | Restriction | Reserve |
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| Links to the text | Library Off-campus access |
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OB00185666 | Springer Business and Management eBooks (電子ブック) | 9781484265161 |
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| Material Type | E-Book |
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| Media type | 機械可読データファイル |
| Size | XVII, 300 p. 131 illus : online resource |
| Notes | Part 1: Introduction -- Chapter 1: Quantum Solutions Overview -- Chapter 2: Mathematics Behind Quantum Computing -- Part 2: Quantum Computing Basics -- Chapter 3: Quantum SubSystems and Properties -- Chapter 4: Quantum Information Processing Framework -- Chapter 5: Quantum Simulators -- Chapter 6: Quantum Optimization Algorithms -- Chapter 7: Quantum Algorithms -- Chapter 8: Quantum Neural Network Algorithms -- Chapter 9: Quantum Classification Algorithms -- Chapter 10: Quantum Data Processing -- Chapter 11: Quantum AI Algorithms -- Chapter 12: Quantum Solutions -- Chapter 13: Evolving Quantum Solutions -- Chapter 14: Next Steps Know how to use quantum computing solutions involving artificial intelligence (AI) algorithms and applications across different disciplines. Quantum solutions involve building quantum algorithms that improve computational tasks within quantum computing, AI, data science, and machine learning. As opposed to quantum computer innovation, quantum solutions offer automation, cost reduction, and other efficiencies to the problems they tackle. Starting with the basics, this book covers subsystems and properties as well as the information processing network before covering quantum simulators. Solutions such as the Traveling Salesman Problem, quantum cryptography, scheduling, and cybersecurity are discussed in step-by-step detail. The book presents code samples based on real-life problems in a variety of industries, such as risk assessment and fraud detection in banking. In pharma, you will look at drug discovery and protein-folding solutions. Supply chain optimization and purchasing solutions are presented in the manufacturing domain. In the area of utilities, energy distribution and optimization problems and solutions are explained. Advertising scheduling and revenue optimization solutions are included from media and technology verticals. You will: Understand the mathematics behind quantum computing Know the solution benefits, such as automation, cost reduction, and efficiencies Be familiar with the quantum subsystems and properties, including states, protocols, operations, and transformations Be aware of the quantum classification algorithms: classifiers, and support and sparse support vector machines Use AI algorithms, including probability, walks, search, deep learning, and parallelism HTTP:URL=https://doi.org/10.1007/978-1-4842-6516-1 |
| Subjects | LCSH:Big data LCSH:Python (Computer program language) LCSH:Quantum computers FREE:Big Data FREE:Python FREE:Quantum Computing |
| Classification | LCC:QA76.9.B45 DC23:005.7 |
| ID | 8000071437 |
| ISBN | 9781484265161 |
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