In-line synthesis of multi-octave phase-stable infrared light
Bibliographic record
Abstract
Parametric downconversion driven by modern, high-power sources of 10-fs-scale near-infrared pulses, in particular intrapulse difference-frequency generation (IPDFG), affords combinations of properties desirable for molecular vibrational spectroscopy in the mid-infrared range: broad spectral coverage, high brilliance, and spatial and temporal coherence. Yet, unifying these in a robust and compact radiation source has remained a key challenge. Here, we address this need by employing IPDFG in a multi-crystal in-line geometry, driven by the 100-W-level, 10.6-fs pulses of a 10.6-MHz-repetition-rate, nonlinearly post-compressed Yb:YAG thin-disk oscillator. Polarization tailoring of the driving pulses using a bichromatic waveplate is followed by a sequence of two crystals, LiIO3 and LiGaS2, resulting in the simultaneous coverage of the 800-cm-1-to-3000-cm-1 spectral range (at -30-dB intensity) with 130 mW of average power. We demonstrate that optical-phase coherence is maintained in this in-line geometry, in theory and experiment, the latter employing ultra-broadband electro-optic sampling. These results pave the way toward coherent spectroscopy schemes like field-resolved and frequency-comb spectroscopy, as well as nonlinear, ultrafast spectroscopy and optical-waveform synthesis across the entire infrared molecular fingerprint region.
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 | 0.001 |
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".