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englund/400zr-coherent-benchmarks

400ZR Coherent Digital Twin Benchmarks This dataset contains comprehensive benchmarks for 400ZR coherent optical transceiver digital twin implementations. ๐Ÿ† Leaderboard (Overall Score) Rank Method Template Overall Score Physics Optimization Reproducibility Standards 1 Silicon_Photonics_v12 v12 0.897 0.895 0.692 1.000 1.000 2 Enhanced_400ZR_v11 v11 0.897 0.895 0.692 1.000 1.000 3 Revolutionary_Framework_v14 v14 0.897 0.895 0.691 1.000 1.000 4โ€ฆ See the full description on the dataset page: https://huggingface.co/datasets/englund/400zr-coherent-benchmarks.

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400ZR Coherent Digital Twin Benchmarks

This dataset contains comprehensive benchmarks for 400ZR coherent optical transceiver digital twin implementations.

๐Ÿ† Leaderboard (Overall Score)

RankMethodTemplateOverall ScorePhysicsOptimizationReproducibilityStandards
1SiliconPhotonicsv12v120.8970.8950.6921.0001.000
2Enhanced400ZRv11v110.8970.8950.6921.0001.000
3RevolutionaryFrameworkv14v140.8970.8950.6911.0001.000
4ComprehensiveResearchv15rv15r0.4280.8770.3330.0000.500
5NonlinearPhysicsv15pv15p0.4280.8770.3330.0000.500

๐Ÿ“Š Evaluation Metrics

Physics Accuracy

  • โ€”OSNR Accuracy: Root mean square error in OSNR prediction (dB)
  • โ€”BER Prediction Error: Relative error in bit error rate prediction
  • โ€”EVM Correlation: Rยฒ correlation coefficient for error vector magnitude

Optimization Performance

  • โ€”Convergence Rate: Fraction of successful optimizations
  • โ€”Convergence Time: Mean time to convergence (milliseconds)
  • โ€”Margin Accuracy: Design margin prediction accuracy

Research Quality

  • โ€”Reproducibility Score: Consistency across multiple runs
  • โ€”Standards Compliance: Compliance with 400ZR specifications

๐Ÿ”„ Reproducibility

All benchmarks use:

  • โ€”Fixed random seed: 42
  • โ€”OSNR range: 10.0 - 35.0 dB
  • โ€”Target BER: 2e-02
  • โ€”M-QAM: 16

๐Ÿ“… Last Updated

2025-08-27 05:01:09 UTC

๐Ÿš€ Contributing

To submit new methods for benchmarking:

  1. 1.Implement the standard 400ZR interface
  2. 2.Submit a pull request with your implementation
  3. 3.Results will be automatically benchmarked and added to the leaderboard

๐Ÿ“„ License

MIT License - See LICENSE file for details