Complete 3D photoelectron momentum vector reconstruction from time-position charged particle imaging
Bibliographic record
Abstract
Abstract Many charged particle imaging techniques exist which directly measure, at a detector, the transverse position (x, y) and time-of-flight (t) of individual events in order to obtain a full set of 3D coordinates. Where curved velocity-mapping electric field lines are implemented, as in the case of 3D Velocity Map Imaging (3D VMI) and certain COLTRIMS (Cold Target Recoil Ion Momentum Spectroscopy) instruments, the general transformation of (x, y, t)-data into initial 3D recoil momentum vectors (px , py , pz ) is challenging and has not yet been fully addressed. Here we present a detailed and general method for this transformation, illustrated using our 3D VMI spectrometer and the well-known narrow-band photoionization of nitric oxide, for which we demonstrate quantitative agreement with reported values. We additionally show how to measure and correct (i) small errors in the laser polarization axis alignment at the interaction region of a 3D charged particle imaging spectrometer, and (ii) the spatial variation of gain on a microchannel plate (MCP) detector. Improvements to and characterization of our 3D VMI spectrometer yield an electron time-of-flight resolution of 72 ps across the full 40 mm MCP, in combination with pixel-level spatial resolution.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".