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Course Outline
Foundations of Quantum Computing
- Key quantum concepts essential for algorithm development.
- Understanding qubits, gates, and measurement processes.
- 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.
Constructing 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
- A solid understanding of core programming concepts.
- Experience with Python or similar programming languages.
- Basic familiarity with quantum computing principles.
Target Audience
- Software Developers
- AI Researchers
- Data Scientists working with emerging technologies
14 Hours
