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Quantum Computing : Research, Applications, and Advances - Arun Sekar Rajasekaran

Quantum Computing

Research, Applications, and Advances

By: Arun Sekar Rajasekaran (Editor), Suganyadevi S. (Editor), Fadi Al-Turjman (Editor)

eText | 16 April 2026 | Edition Number 1

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Quantum computing is a rapidly emerging technology that harnesses the laws of quantum mechanics to solve problems too complex for classical computers. It is a multidisciplinary field comprising aspects of computer science, physics, and mathematics that utilizes quantum mechanics to solve complex problems faster than classical computers. It is a computational technology that uses the principles of quantum mechanics, such as entanglement, superposition, and interference to process, store, and manipulate large amounts of data and perform complex calculations for conventional computing systems and supercomputers cannot fathom.

Quantum Computing: Research, Applications, and Advances provides a comprehensive overview of the foundational principles of quantum mechanics that underpin quantum computing. It explains such concepts as superposition, entanglement, and quantum gates to demystify the esoteric nature of quantum phenomena. It delves into the current state of quantum computing research, presenting an insightful analysis of the latest breakthroughs and technological advancements. From the race to achieve quantum supremacy to the development of scalable quantum hardware, the book offers a detailed exploration of the key players, their methodologies, and the challenges they face in pushing the boundaries of quantum computing capabilities. It explores the practical applications of quantum computing across various domains. From cryptography to optimization problems and drug discovery, the book also illustrates how quantum algorithms have the potential to outperform classical counterparts to open doors to new possibilities where traditional computing falls short. The book integrates theoretical concepts and practical applications. The highlights include the following:

  • Quantum computing in machine learning
  • Harnessing quantum computing for predictive analysis
  • Quantum-powered financial fraud detection
  • Enhancing deep learning with quantum computing
  • Quantum computing in medical imaging
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