Quantum Computing In Data Science And Analytics: An Overview

Quantum computing is highly effective in processing the large amounts of data being generated by AI-based systems.

Quantum computing focuses on quantum-based information processing including cryptography, pattern recognition, strategic decision making under constraints, and many similar sensitive and performance-based applications. Table 1 lists its key uses and the algorithms developed for them.

Table 1: Key uses of quantum computing

Quantum computing can be implemented in a range of domains in which supercomputing-like performance is required.

• AI and ML: Pattern recognition, Quantum machine learning (QML), Machine learning, Recommendation systems, Natural language processing (NLP)
• Autonomous systems: Autonomous vehicle decision making, Optimization
• Aviation: Airline scheduling, Optimization
• Chemistry: Computational chemistry, Process simulation
• Climate science: Weather modelling and climate simulations
• Cybersecurity: Code breaking (Shor’s Algorithm), Cryptanalysis, Cryptography, Quantum Key Distribution (QKD), Quantum communication
• Data science: Big Data analytics, Search and optimization
• Disaster management: Earthquake and disaster prediction
• Electronics: Semiconductor design, Circuit simulation
• Energy: Energy optimization, Smart grid management
• Finance: Financial portfolio optimization, Finance fraud detection, Risk analysis and Monte Carlo simulations, Data sampling
• Healthcare: Drug discovery, Process reaction simulation, Genomics and precision medicine, Healthcare diagnostics, Protein folding analysis
• Industry 4.0 and Industry 5.0: Quantum digital twins and simulation
• IoT: Network optimization, Smart city simulation, Resource optimization
• Logistics: Supply chain management and optimization
• Manufacturing: Process optimization
• Robotics: Path planning, Resource optimization
• Smart cities: Urban planning optimization, Traffic flow management
• Space: Space communication, Satellite communication and optimization, Space mission planning
• Telecommunications: Telecommunication network optimization
• Transportation: Vehicle routing problems and resource allocation