Multispectral multidimensional spectrometer spanning the ultraviolet to the mid-infrared
Bibliographic record
Abstract
Multidimensional spectroscopy is the optical analog to nuclear magnetic resonance, probing dynamical processes with ultrafast time resolution. At optical frequencies, the technical challenges of multidimensional spectroscopy have hindered its progress until recently, where advances in laser sources and pulse-shaping have removed many obstacles to its implementation. Multidimensional spectroscopy in the visible and infrared (IR) regimes has already enabled respective advances in our understanding of photosynthesis and the structural rearrangements of liquid water. A frontier of ultrafast spectroscopy is to extend and combine multidimensional techniques and frequency ranges, which have been largely restricted to operating in the distinct visible or IR regimes. By employing two independent amplifiers seeded by a single oscillator, it is straightforward to span a wide range of time scales (femtoseconds to seconds), all of which are often relevant to the most important energy conversion and catalysis problems in chemistry, physics, and materials science. Complex condensed phase systems have optical transitions spanning the ultraviolet (UV) to the IR and exhibit dynamics relevant to function on time scales of femtoseconds to seconds and beyond. We describe the development of the Multispectral Multidimensional Nonlinear Spectrometer (MMDS) to enable studies of dynamical processes in atomic, molecular, and material systems spanning femtoseconds to seconds, from the UV to the IR regimes. The MMDS employs pulse-shaping methods to provide an easy-to-use instrument with an unprecedented spectral range that enables unique combination spectroscopies. We demonstrate the multispectral capabilities of the MMDS on several model systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".