Coherent control of the population transfer in complex solvated molecules at weak excitation. An experimental study
Bibliographic record
Abstract
We performed a series of successful experiments for the optimization of the population transfer from the ground to the first excited state in a complex solvated molecule (rhodamine 101 in methanol) using shaped excitation pulses at very low intensities (1 absorbed photon per 100-500 molecules per pulse). We found that the population transfer can be controlled and significantly enhanced by applying excitation laser pulses with crafted pulse shapes. The optimal shape was found in feedback-controlled experiments using a genetic search algorithm. The temporal profile of the optimal excitation pulse corresponds to a comb of subpulses regularly spaced by approximately 150 fs, whereas its spectrum consists of a series of well-resolved peaks spaced apart by approximately 6.5 nm corresponding to a frequency of 220 cm(-1). This frequency matches very well with the frequency modulation of the population kinetics (period of approximately 150 fs), observed by excitation with a short (approximately 20 fs) transform-limited laser pulse directly after excitation. In addition, an antioptimization experiment was performed under the same conditions. The difference in the population of the excited state for the optimal and antioptimal pulses reaches approximately 30% even at very weak excitation. The results of optimization are reproducible and have clear physical meaning.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".