Towards simultaneous imaging of ultrafast nuclear and electronic dynamics in small molecules
Bibliographic record
Abstract
Abstract When a chemical bond is broken, the molecular structure undergoes a transformation. An ideal experiment should probe the change in the electronic and nuclear structure simultaneously. Here, we present a method for the simultaneous time-resolved imaging of nuclear and electron dynamics by combining Coulomb explosion imaging with strong-field photoelectron momentum imaging. We study the dissociative photoionization of H2 and N2O using time-resolved photoion-photoelectron coincidence spectroscopy. The measured delay-dependent kinetic energy release clearly reveals the ultrafast nuclear dynamics. The transient changes in the electronic structure of the dissociating $$\hbox {H}_2^+$$ molecular ion are studied by solving the three-dimensional Schrödinger equation in the fixed-nuclei approximation. A detailed comparison of the numerical results to those from a simple imaging model is conducted. The numerical results reflect the evolution in the electron density in the molecular ion as its bond is first stretched and then breaks apart. While these details remain unresolved in the H2 experiment, we demonstrate the sensitivity of the photoelectron signal to the site of electron localization following bond cleavage for the case of N2O. Our work shows opportunities and challenges on the track towards capturing simple gas-phase chemical dynamics in complete molecular movies.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".