Net 350 Gbps/λ IMDD Transmission Enabled by High Bandwidth Thin-Film Lithium Niobate MZM
Bibliographic record
Abstract
We demonstrate ultra-high-speed data transmission at a symbol rate up to 144 Gbaud using thin-film lithium niobate (TFLN) modulator in an intensity modulation direct-detection (IMDD) system. With 95 GHz 6-dB electro-optic bandwidth and 1.5 V half-wave voltage, this C-band modulator enables the transmission of net 318 (308) Gbps PAM-6 at B2B (after 500 m of standard single-mode fiber) below the 6.7% overhead (OH) hard-decision forward error correction (HD-FEC) BER threshold of$3.8\times 10 ^{-3}$. We also transmit net 360 (350) Gbps PAM-8 at B2B (500 m), which satisfies the normalized generalized mutual information (NGMI) threshold of 0.8798 with 19.02% overhead soft-decision (SD) FEC. To the best of our knowledge, this is the first demonstration of net 300 Gbps below the 6.7% OH HD-FEC BER threshold and the highest net rate (360 Gbps) achieved on the TFLN platform using pulse amplitude modulation (PAM).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".