Name: Quantum Machine Learning in Industrial Automation
SKU: 64766706
Price: 6373.00 TWD
Availability: InStock
Author: Anupam Ghosh;Vinod Kumar Shukla;Soumi Dutta;Fernando Moreira;Asit Kumar Das
ISBN: 9783031997853

portada Quantum Machine Learning in Industrial Automation

Quantum Machine Learning in Industrial Automation

Type

Physical Book

Publisher

Springer International Publishing AG

Author

Anupam Ghosh;Vinod Kumar Shukla;Soumi Dutta;Fernando Moreira;Asit Kumar Das

Collection

Information Systems Engineering and Management

Year

2025

Pages

456

Format

Hardcover

Dimensions

23.5x15.5 cm

ISBN13

9783031997853

Quantum Machine Learning in Industrial Automation

Anupam Ghosh;Vinod Kumar Shukla;Soumi Dutta;Fernando Moreira;Asit Kumar Das (Author) · Springer International Publishing AG · Hardcover

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Synopsis "Quantum Machine Learning in Industrial Automation"

This book focuses on quantum machine learning that harnesses the collective properties of quantum states, such as superposition, interference, and entanglement, uses algorithms run on quantum devices, such as quantum computers, to supplement, expedite, or support the work performed by a classical machine learning program. The devices that perform quantum computations are known as quantum computers. Quantum computers have the potential to revolutionize computation by making certain types of classically intractable problems solvable. A few large companies and small start-ups now have functioning non-error-corrected quantum computers composed of several tens of qubits, and some of these are even accessible to the public through the cloud. Additionally, quantum simulators are making strides in fields varying from molecular energetics to many-body physics. Most known use cases fit into four archetypes: quantum simulation, quantum linear algebra for AI and machine learning, quantum optimization and search, and quantum factorization. Advantages of quantum computing are many and to list a few, first, they’re fast. Ultimately, quantum computers have the potential to provide computational power on a scale that traditional computers cannot ever match. In 2019, for example, Google claimed to carry out a calculation in about 200 seconds that would take a classical supercomputer around 10,000 years. Second, they can solve complex problems. The more complex a problem, the harder it is for even a supercomputer to solve. When a classical computer fails, it’s usually because of a huge degree of complexity and many interacting variables. However, due to the concepts of superposition and entanglement, quantum computers can account for all these variables and complexities to reach a solution. Last but not the least, they can run complex simulations. The speed and complexity that quantum computing can achieve means that, in theory, a quantum computer could simulate many intricate systems.