quantum-nsn-integration / QUICK_START.md
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NSN Integration Quick Start Guide

Get started with NSN integration in 5 minutes!

Installation

No additional dependencies required. The NSN integration uses existing quantum_integration packages.

Quick Examples

1. Backend-Aware Rank Selection (30 seconds)

from quantum_integration.nsn_integration import BackendAwareRankSelector, BackendType

selector = BackendAwareRankSelector()
recommendation = selector.get_rank_recommendation(
    backend_type=BackendType.IBM_WASHINGTON,
    compute_budget=1e8,
    min_reliability=0.85
)

print(f"Recommended Rank: {recommendation['recommended_rank']}")
print(f"Rationale: {recommendation['rationale']}")

2. Multilingual Evaluation (1 minute)

from quantum_integration.nsn_integration import MultilingualNSNEvaluator

evaluator = MultilingualNSNEvaluator()
result = evaluator.evaluate_language_edit('indonesian', rank=64)

print(f"Accuracy: {result.edit_accuracy:.3f}")
print(f"Uncertainty: {result.uncertainty:.3f}")

3. Contributor Challenge (2 minutes)

from quantum_integration.nsn_integration import NSNLeaderboard

leaderboard = NSNLeaderboard()
challenge = leaderboard.create_challenge(
    challenge_id="my_challenge",
    title="My First Challenge",
    description="Test multilingual editing",
    languages=['english', 'chinese']
)

# Submit edit
rank_results = {
    32: {'accuracy': 0.88, 'uncertainty': 0.12, 'flops': 1e7, 'efficiency': 0.009}
}

submission = leaderboard.submit_edit(
    challenge_id="my_challenge",
    contributor_id="me",
    language="english",
    edit_description="My edit",
    rank_results=rank_results
)

rankings = leaderboard.get_leaderboard("my_challenge")
print(f"Position: {rankings[0]['position']}")

Run Complete Demo

python quantum_integration/nsn_integration/demo_complete_nsn_integration.py

Run Tests

python quantum_integration/nsn_integration/test_nsn_integration.py

Next Steps

  • Read the full README.md for detailed documentation
  • Explore visualization with NSNDashboard
  • Integrate with LIMIT-Graph benchmarking
  • Submit to contributor challenges

Support

Check the README.md or open an issue for help!