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Record W2030531807 · doi:10.1063/1.1886750

Coherent control of the population transfer in complex solvated molecules at weak excitation. An experimental study

2005· article· en· W2030531807 on OpenAlexaff
Valentyn I. Prokhorenko, Andrea M. Nagy, R. J. Miller

Bibliographic record

VenueThe Journal of Chemical Physics · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExcitationExcited statePopulationAtomic physicsPulse (music)LaserPopulation inversionGround stateChemistryMolecular physicsMaterials sciencePhysicsOptics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.180

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.293
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations74
Published2005
Admission routes1
Has abstractyes

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