1. Algorithm Development

[shef4]

Goal: Optimize and test the algorithm to ensure efficiency and accuracy.

Actionable Tasks:
1. Set Up Development Environment:
• Create a dedicated GitHub repository for the project.
• Set up folders for code, results, and documentation.
2. Develop the Base Algorithm:
• Write the initial implementation of the sieve using wavefunction principles.
• Test the algorithm with small prime ranges for validation.
3. Optimize Algorithm:
• Identify bottlenecks using profiling tools (e.g., Python’s cProfile, MATLAB profiler).
• Explore optimization strategies (e.g., parallelization, memory management).
4. Test with Larger Datasets:
• Run the algorithm on larger datasets to measure performance.
• Compare results with traditional sieve methods (e.g., classical Sieve of Eratosthenes).
5. Document Observations:
• Record performance metrics (e.g., runtime, memory usage).
• Note any deviations or edge cases that require further analysis.
6. Prepare Visualizations:
• Create plots or graphs showing efficiency gains (e.g., runtime vs dataset size).
• Develop animations or visuals explaining the wavefunction-inspired process.