Impulsive stimulated Raman scattering imaging using an ultra-fast acoustic-optics delay line
Bibliographic record
Abstract
vibrational motion of a molecule is intrinsically linked to its structure and composition, which provides a way to identify it. Raman spectroscopy, utilizing the inelastic scattering of light, investigates these molecular vibrations. While Raman shifts exceeding 200 cm−1 primarily capture intramolecular vibrations, lower Raman shifts ( < 200 cm−1) provide insights into the collective motion of molecules, thereby revealing valuable structural information. Although frequency domain imaging effectively addresses higher Raman shifts, a time domain approach proves more practical for lower Raman shifts. Impulsive Stimulated Raman Scattering (ISRS) is a time domain technique that employs a pump pulse to instantaneously excite a molecule, activating all modes within its bandwidth and inducing a transient refractive index modulation. This modulation can be probed by a second pulse, enabling analysis of spatial profile, spectrum, and polarization changes. In this study, we elucidate the implementation of transient vibrational refractive index detection for the acquisition of ultrafast hyperspectral images, including the integration of a random access delay line into the existing setup that enables scanning windows of up to 50 picoseconds at random time delays.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".