Enhancement Request
Add a comprehensive comparison table showing the computational complexity, memory requirements, and use cases for all supported quantum algorithms.
Motivation
New users often ask "which algorithm should I use?" but have to dig through code comments to understand the trade-offs between QFT, Grover, Shor, GHZ, and Bell algorithms.
Proposed Addition
Add this table to the README.md in the "Advanced Algorithms" section:
| Algorithm |
Time Complexity |
Memory Usage |
Best For |
Max Qubits* |
| QFT |
O(n²) gates |
Most efficient |
Shor's algorithm, frequency analysis |
25+ |
| Grover |
O(√N) iterations |
Moderate |
Database search, optimization |
20+ |
| Shor |
O(n³) gates |
High |
Factorization, cryptography |
18+ |
| GHZ |
O(n) gates |
Light |
Multi-party entanglement |
25+ |
| Bell |
O(n) gates |
Lightest |
Basic entanglement, benchmarking |
25+ |
*Approximate limits on typical hardware
Additional Documentation Needed
- Brief explanation of when to use each algorithm
- Link to relevant research papers
- Performance benchmarks on different hardware
Implementation Notes
- Good first issue for new contributors
- Requires no code changes, only documentation
- Should match the current performance characteristics in
test_ultimate_scaling.py
Acceptance Criteria
Enhancement Request
Add a comprehensive comparison table showing the computational complexity, memory requirements, and use cases for all supported quantum algorithms.
Motivation
New users often ask "which algorithm should I use?" but have to dig through code comments to understand the trade-offs between QFT, Grover, Shor, GHZ, and Bell algorithms.
Proposed Addition
Add this table to the README.md in the "Advanced Algorithms" section:
*Approximate limits on typical hardware
Additional Documentation Needed
Implementation Notes
test_ultimate_scaling.pyAcceptance Criteria