Electronic State Population Dynamics upon Ultrafast Strong Field Ionization and Fragmentation of Molecular Nitrogen
Bibliographic record
Abstract
Air lasing from single ionized ${\mathrm{N}}_{2}^{+}$ molecules induced by laser filamentation in air has been intensively investigated and the mechanisms responsible for lasing are currently highly debated. We use ultrafast nitrogen $K$-edge spectroscopy to follow the strong field ionization and fragmentation dynamics of ${\mathrm{N}}_{2}$ upon interaction with an ultrashort 800 nm laser pulse. Using probe pulses generated by extreme high-order harmonic generation, we observe transitions indicative of the formation of the electronic ground $X^{2}{\mathrm{\ensuremath{\Sigma}}}_{g}^{+}$, first excited $A{^{2}\mathrm{\ensuremath{\Pi}}}_{u}$, and second excited $B^{2}{\mathrm{\ensuremath{\Sigma}}}_{u}^{+}$ states of ${\mathrm{N}}_{2}^{+}$ on femtosecond timescales, from which we can quantitatively determine the time-dependent electronic state population distribution dynamics of ${\mathrm{N}}_{2}^{+}$. Our results show a remarkably low population of the $A^{2}{\mathrm{\ensuremath{\Pi}}}_{u}$ state, and nearly equal populations of the $X^{2}{\mathrm{\ensuremath{\Sigma}}}_{g}^{+}$ and $B^{2}{\mathrm{\ensuremath{\Sigma}}}_{u}^{+}$ states. In addition, we observe fragmentation of ${\mathrm{N}}_{2}^{+}$ into N and ${\mathrm{N}}^{+}$ on a timescale of several tens of picoseconds that we assign to significant collisional dynamics in the plasma, resulting in dissociative excitation of ${\mathrm{N}}_{2}^{+}$.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".