Chapter 5: Quantum Computing-Transforming Technology

Introduction:

• Quantum computing differs from regular computing in that it represents information with 'bits'—binary digits of Os and 1 s.
• However, quantum computing employs quantum bits, or 'qubits,' which can exist in several states at the same time, rather than just two (i.e., 0 and 1).
• This'superposition' feature of qubits enables quantum computers to do many computational calculations orders of magnitude faster than classical computers.
• Furthermore, quantum computing draws inspiration from another aspect of quantum mechanics known as entanglement, in which two qubits can be coupled in such a way that the state of one qubit affects the state of the other.

Quantum Computing's Impact:

• Given India's growing capabilities in information technology (IT) and IT-enabled services, the future of quantum computing will drastically transform the skill needs and capabilities of the emerging skill force, which is gradually ramping up in data science, artificial intelligence, machine learning, and decision sciences.
• In industrial data science applications, faster data analysis: Certain types of calculations can be performed substantially faster by quantum computers than by classical computing logic. As the scope and size of these computations grow, they may enable faster data analysis for business challenges in the age of big data, particularly for enormous datasets collected at high velocity.
• Improved machine learning results: Machine learning algorithms are increasingly being employed to improve prediction skills and data-driven decision-making.
• In the age of cognitive computing, these algorithms may concentrate on complicated data types such as photos and videos to solve corporate and social problems via areas such as computer vision.
• Quantum computers have the potential to improve machine learning by enabling more efficient optimisation of these algorithms, resulting in more efficient, accurate, and quick computer vision capabilities.
• Furthermore, in generative artificial intelligence applications, quantum computing could deliver superior suggestions since it is possible to develop architectures that examine real-time contributions to the digital world's web of information to create guidance.
• Improved optimisation for complicated problems: Finding the best solution to a complex problem is a common task in analytics.Quantum computers may be able to tackle these problems much faster than traditional computers, allowing for more effective optimisation of complex systems.
• Improved industrialisation: Quantum computing would enable the realisation of industrial maturity levels such as Industry 4.0 and beyond via platforms such as digital twins. Distributed computing networks, federated learning, the "Internet of Everything," blockchain, and other related technologies are expected to grow more efficient in terms of reaching their desired computational and quality outcomes.

Policy and practise implications:

• Quantum computing is an advanced field in which research and development are still in their early stages.
• This, however, provides a chance for India to build well-funded Research Centres of Excellence in premier technology universities.
• Long-term plans of the Department of Science and Technology might be implemented, through which strategic infrastructure and personnel training initiatives in established technology engineering institutes could be sponsored.
• To further create a homegrown quantum technology industry, this would need to include both hardware and software.