Advancing High-Power Hollow-Core Fiber Pulse Compression
Bibliographic record
Abstract
Ultrafast laser science witnesses a transformative change due to the introduction of robust, high repetition rate Yb based solid state lasers. We prove the ability of hollow-core fiber (HCF) post compression to keep pace with the constantly raising average powers and pulse energies provided by state-of-the-art lasers. Over a wide range of input parameters, HCFs can provide high transmissions in the 80%–90% range with greater than 10-fold compression. First, we describe a double stage HCF setup that compresses 80 W, 2 mJ, 338 fs pulses centered at 1030 nm down to sub-two optical cycles (6 fs FWHM) with 56 W output power. This 56-fold pulse compression is paired with an overall throughput of 70% and very good long term stability (1.5% StDev over 8 hours). Next, power scaling to 300 W with variable pulse energy and repetition rate (from 100 kHz, 3 mJ to 25 kHz, 12 mJ) is presented. We compressed 1.3 ps pulses of down to 100 fs in a single HCF at 300 W level. Finally, we reveal the potential of utilizing the ultrabroadband HCF output as a spectroscopy platform that can provide various, simultaneous outputs covering a wavelength range from 430 nm up to 12$\mu$m.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".