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Course Outline
Quantum Computing Foundations
- Key quantum concepts for algorithm development
- Understanding qubits, gates, and measurements
- The role of quantum circuits in computation
Introduction to Google Willow
- Exploring the Willow workspace
- Working with simulators and quantum hardware
- Managing tasks and computational resources
Building Quantum Circuits
- Designing parameterized circuits
- Manipulating gates and operations
- Executing simple circuits on Willow
Implementing Core Quantum Algorithms
- Constructing algorithms such as Grover’s and QFT
- Analyzing algorithm behavior on hardware
- Comparing classical and quantum performance
Advanced Algorithm Design
- Creating problem-specific circuits
- Integrating noise-mitigation techniques
- Scaling and optimizing circuit depth
Hybrid Quantum-Classical Workflows
- Using Python libraries to orchestrate workflows
- Connecting classical code with Willow executions
- Building reusable algorithmic components
Testing, Debugging, and Optimization
- Debugging circuits using simulator tools
- Profiling quantum algorithm performance
- Applying optimization strategies
Deploying Quantum Algorithms
- Submitting tasks through the Willow interface
- Reviewing execution outcomes
- Iterating on algorithm improvements
Summary and Next Steps
Requirements
- An understanding of core programming concepts
- Experience with Python or similar languages
- Basic familiarity with quantum computing principles
Audience
- Developers
- AI researchers
- Data scientists working with emerging technologies
14 Hours
