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Chapter 11 Quantum computing and machine learning: a symbiotic relationship

  • Asif Ali and Priyanka Vashisht
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Industrial Quantum Computing
This chapter is in the book Industrial Quantum Computing

Abstract

Quantum computing and machine learning are probably the most likely to replace classical computers. The power of quantum computers can, for example, change communication can be mentioned, as well as the use of some quantum phenomena as well. This is how, finally, we get the possibility of completely safe communication. Furthermore, quantum computer simulators can be used to enhance knowledge about numerous quantum outcomes, which in return will help engineers develop the technologies of tomorrow, such as power systems, microchips, and modern scientific tools. However, it is worth mentioning that this technology is different from traditional computers in terms of the presence and use of qubits instead of bits. It is precisely due to this leap in computing power that quantum computers can now complete problems in a much shorter time. They do so by looking for the most favorable paths in modeling the orbits. Ironically, their low capabilities are associated with the fact that they were designed to deal with complexity and constraints; they still wouldn’t be preferred for performing rather simple tasks compared to classical computers. The top priority for quantum computers is to perform their functions properly. The real impact of quantum computing is not in the technology itself but in the subsequent applications that come about as a result of it. Therefore, size and quantum error correction, as well as the development of quantum algorithms, will be the dominant constraints in making these methods more widely accessible. Similarly, limitless abilities are simultaneously incorporated with quantum computing; however, effort should be made either in optimization or development if that potential is to become the most powerful.

Abstract

Quantum computing and machine learning are probably the most likely to replace classical computers. The power of quantum computers can, for example, change communication can be mentioned, as well as the use of some quantum phenomena as well. This is how, finally, we get the possibility of completely safe communication. Furthermore, quantum computer simulators can be used to enhance knowledge about numerous quantum outcomes, which in return will help engineers develop the technologies of tomorrow, such as power systems, microchips, and modern scientific tools. However, it is worth mentioning that this technology is different from traditional computers in terms of the presence and use of qubits instead of bits. It is precisely due to this leap in computing power that quantum computers can now complete problems in a much shorter time. They do so by looking for the most favorable paths in modeling the orbits. Ironically, their low capabilities are associated with the fact that they were designed to deal with complexity and constraints; they still wouldn’t be preferred for performing rather simple tasks compared to classical computers. The top priority for quantum computers is to perform their functions properly. The real impact of quantum computing is not in the technology itself but in the subsequent applications that come about as a result of it. Therefore, size and quantum error correction, as well as the development of quantum algorithms, will be the dominant constraints in making these methods more widely accessible. Similarly, limitless abilities are simultaneously incorporated with quantum computing; however, effort should be made either in optimization or development if that potential is to become the most powerful.

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. List of contributors VII
  4. Chapter 1 Quantum computing in society: impacts and implications 1
  5. Chapter 2 Quantum computing with machine learning: opportunities and challenges 19
  6. Chapter 3 Quantum machine learning algorithms: a comprehensive review 37
  7. Chapter 4 Highlighting major issues with quantum computing in healthcare 53
  8. Chapter 5 Privacy and security for 6G’s IoT-connected future in the age of quantum computing 67
  9. Chapter 6 Can quantum computers revolutionize health systems? 87
  10. Chapter 7 Industrial automation and quantum computing 105
  11. Chapter 8 Applications of quantum computing in financial planning and financial control 127
  12. Chapter 9 Quantum computing in machine learning: an overview 141
  13. 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
  14. Chapter 11 Quantum computing and machine learning: a symbiotic relationship 177
  15. Chapter 12 Quantum-secured healthcare data and cybersecurity innovations in the era of Industry 5.0 199
  16. Chapter 13 Introduction to quantum computing and its revolution in industry and society 219
  17. Chapter 14 Advancing healthcare through the opportunities and challenges of quantum computing 239
  18. Chapter 15 Quantum computing in drug and chemical 255
  19. Index 279
https://doi.org/10.1515/9783111354842-011

Chapters in this book

  1. Frontmatter I
  2. Contents V
  3. List of contributors VII
  4. Chapter 1 Quantum computing in society: impacts and implications 1
  5. Chapter 2 Quantum computing with machine learning: opportunities and challenges 19
  6. Chapter 3 Quantum machine learning algorithms: a comprehensive review 37
  7. Chapter 4 Highlighting major issues with quantum computing in healthcare 53
  8. Chapter 5 Privacy and security for 6G’s IoT-connected future in the age of quantum computing 67
  9. Chapter 6 Can quantum computers revolutionize health systems? 87
  10. Chapter 7 Industrial automation and quantum computing 105
  11. Chapter 8 Applications of quantum computing in financial planning and financial control 127
  12. Chapter 9 Quantum computing in machine learning: an overview 141
  13. 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
  14. Chapter 11 Quantum computing and machine learning: a symbiotic relationship 177
  15. Chapter 12 Quantum-secured healthcare data and cybersecurity innovations in the era of Industry 5.0 199
  16. Chapter 13 Introduction to quantum computing and its revolution in industry and society 219
  17. Chapter 14 Advancing healthcare through the opportunities and challenges of quantum computing 239
  18. Chapter 15 Quantum computing in drug and chemical 255
  19. Index 279
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