Calculation of bit error ratio for optically pre-amplified DPSK receivers using optical Mach-Zehnder interferometer demodulation and balanced detection
Bibliographic record
Abstract
This paper presents an analysis of how to calculate bit error ratio (BER) with physical explanation for optically pre-amplified DPSK receivers using optical Mach-Zehnder interferometer (MZI) demodulation and balanced detection. It is shown that BER calculation method for this kind of receivers is different from the conventional calculation method used widely for IM/DD receivers. An analytical relationship in receiver sensitivity between DPSK receivers using MZI demodulation with balanced detection and IM/DD receivers (or DPSK receivers using MZI demodulation and single-port detection) is given based on the Gaussian noise approximation. Our calculation method correctly predicts the 3-dB improvement of receiver sensitivity by using balanced detection over single-port detection or IM/DD receivers. This predicted 3-dB improvement by using balanced detection converges with the interpretation of the 3-dB improvement by signal constellation. Furthermore, quantum-limited DPSK receivers with MZI demodulation are also analyzed in Appendix B.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".