Chapter 15 Quantum computing in drug and chemical
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Bijeta Seth
Abstract
Quantum computing, which combines physics, software engineering, and mathematics, has the potential to change many industries with its unrivaled processing capacity. This article covers quantum computing’s fundamentals, recent advances, future applications, and challenges. We research the fundamental quantum physics principles of quantum computing. We study quantum gates, entanglement, and superposition. Next, we examine quantum computer applications employing qubits and quantum circuits. Several qubit-making physical systems will also be examined. We also examine the rapidly changing environment of various quantum algorithms, such as Grover’s unstructured search and Shor’s integer factorization approaches, and their effects on machine learning, optimization, and cryptography. We also thoroughly study quantum error correction and fault-tolerance advances that mitigate decoherence and noise in quantum systems. We also investigate the fast-growing field of quantum software development, including programming languages, simulators, and compilers. We conclude by assessing the barriers to scaling up and implementing quantum computers. Error rates, qubit coherence duration, and scalable quantum hardware architectures are these challenges. This study tries to understand quantum computing’s complex field, revealing its transformative potential and guiding future research.
Abstract
Quantum computing, which combines physics, software engineering, and mathematics, has the potential to change many industries with its unrivaled processing capacity. This article covers quantum computing’s fundamentals, recent advances, future applications, and challenges. We research the fundamental quantum physics principles of quantum computing. We study quantum gates, entanglement, and superposition. Next, we examine quantum computer applications employing qubits and quantum circuits. Several qubit-making physical systems will also be examined. We also examine the rapidly changing environment of various quantum algorithms, such as Grover’s unstructured search and Shor’s integer factorization approaches, and their effects on machine learning, optimization, and cryptography. We also thoroughly study quantum error correction and fault-tolerance advances that mitigate decoherence and noise in quantum systems. We also investigate the fast-growing field of quantum software development, including programming languages, simulators, and compilers. We conclude by assessing the barriers to scaling up and implementing quantum computers. Error rates, qubit coherence duration, and scalable quantum hardware architectures are these challenges. This study tries to understand quantum computing’s complex field, revealing its transformative potential and guiding future research.
Chapters in this book
- Frontmatter I
- Contents V
- List of contributors VII
- Chapter 1 Quantum computing in society: impacts and implications 1
- Chapter 2 Quantum computing with machine learning: opportunities and challenges 19
- Chapter 3 Quantum machine learning algorithms: a comprehensive review 37
- Chapter 4 Highlighting major issues with quantum computing in healthcare 53
- Chapter 5 Privacy and security for 6G’s IoT-connected future in the age of quantum computing 67
- Chapter 6 Can quantum computers revolutionize health systems? 87
- Chapter 7 Industrial automation and quantum computing 105
- Chapter 8 Applications of quantum computing in financial planning and financial control 127
- Chapter 9 Quantum computing in machine learning: an overview 141
- Chapter 10 The impact of AI and automation on income inequality in BRICS countries and the role of structural factors and women’s empowerment 155
- Chapter 11 Quantum computing and machine learning: a symbiotic relationship 177
- Chapter 12 Quantum-secured healthcare data and cybersecurity innovations in the era of Industry 5.0 199
- Chapter 13 Introduction to quantum computing and its revolution in industry and society 219
- Chapter 14 Advancing healthcare through the opportunities and challenges of quantum computing 239
- Chapter 15 Quantum computing in drug and chemical 255
- Index 279
Chapters in this book
- Frontmatter I
- Contents V
- List of contributors VII
- Chapter 1 Quantum computing in society: impacts and implications 1
- Chapter 2 Quantum computing with machine learning: opportunities and challenges 19
- Chapter 3 Quantum machine learning algorithms: a comprehensive review 37
- Chapter 4 Highlighting major issues with quantum computing in healthcare 53
- Chapter 5 Privacy and security for 6G’s IoT-connected future in the age of quantum computing 67
- Chapter 6 Can quantum computers revolutionize health systems? 87
- Chapter 7 Industrial automation and quantum computing 105
- Chapter 8 Applications of quantum computing in financial planning and financial control 127
- Chapter 9 Quantum computing in machine learning: an overview 141
- Chapter 10 The impact of AI and automation on income inequality in BRICS countries and the role of structural factors and women’s empowerment 155
- Chapter 11 Quantum computing and machine learning: a symbiotic relationship 177
- Chapter 12 Quantum-secured healthcare data and cybersecurity innovations in the era of Industry 5.0 199
- Chapter 13 Introduction to quantum computing and its revolution in industry and society 219
- Chapter 14 Advancing healthcare through the opportunities and challenges of quantum computing 239
- Chapter 15 Quantum computing in drug and chemical 255
- Index 279
