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

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