Terahertz Comb generation via laser-cavity soliton microcombs
Bibliographic record
Abstract
Miniaturised chip-scale platforms capable of generating broadband, low-noise millimetre-wave (mm-wave) and terahertz signals can enable new forms of wireless synchronisation in communication, advanced metrology, and high-resolution THz spectroscopy. We demonstrate the laser cavity soliton first broadband mm-wave comb generated directly from a Laser Cavity Soliton (LCS) microcomb, spanning three octaves. The inherent high spectral efficiency of the LCS state and the lack of intrinsic CW background enable the generation of mm-wave combs through photomixing-rectification of the optical pulses. This preserves multiple harmonics above the fundamental beatnote over a 500GHz detectable bandwidth. The control of LCS-soliton properties results in the manipulation of the THz pulse amplitude, phase, and spectral line fine-spacing. We show that locking the microcomb repetition rate to a GPS reference drastically improves the phase noise of optical intensity signal which feeds into the frequency stability of the mm-wave comb, establishing a practical path forward to miniaturised, metrological THz comb sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".