Reconstructing real-space geometries of polyatomic molecules undergoing strong field laser-induced Coulomb explosion
Bibliographic record
Abstract
Coulomb explosion is an established momentum imaging technique, where the molecules are ionized multiple times on a femtosecond time scale before breaking up into ionized fragments. By measuring the momentum of all the ions, information about the initial molecular structure is theoretically available. However, significant geometric changes due to multiple ionizations occur before the explosion, posing a challenge in retrieving the ground-state structure of molecules from the measured momentum values of the fragments. In this work, we investigate theoretically and experimentally such a connection between the ground-state geometry of a polyatomic molecule (OCS) and the detected momenta of ionic fragments from the Coulomb explosion. By relying on time-dependent density functional theory (TDDFT), we can rigorously model the ionization dynamics of the molecule in the tunneling regime. We reproduce the energy release and the Newton plot momentum patterns of an experiment in which OCS is ionized to the 6+ charge state. Our results provide insight into the behavior of molecules during strong field multiple ionization, opening a way toward precision imaging of real-space molecular geometries using tabletop lasers. Understanding molecular structure and dynamics through strong-field laser interactions holds great promise. The authors use quantum calculations to show how bonds and angles evolve in an OCS molecule ionized six times by a 7 fs, 800 nm laser pulse, accurately predicting our experimental results.
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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 | 0.001 |
| 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".