Modeling of the Photoelectron Space-Energy Distribution Based on a Contemporary Coupled Photon-Electron Transport Approach
Bibliographic record
Abstract
Photoelectrons produced by solar EUV uxes are a major contributor to ionospheric heating at high altitudes. Modeling of photoelectron heating relies strongly on their space-energy distribution, which in turn depends on the accuracy of the description of EUV sources and complex photon-electron transport. The source of EUV uxes is solar radiation emitted from the whole solar disk and corrected for atmospheric absorption. Measured EUV uxes consist of numerous integrated bands and the emission line intensities, which have high (~50%) variability, even for similar levels of solar activity (Heroux, 1972). We analyze the sensitivity of photoelectron production to the EUV sources by comparing results calculated based on a direct EUV ux measurement in the wavelength region 1220-52 Å from(Heroux, 1972), and the EUVAC model developed by Phil Richards (Richards et al., 1994). Our preliminary results show that the accuracy of the EUVAC model in the calculation of the photoelectron space-energy distribution is comparable to that based on direct EUV ux measurements. Photoelectron production caused by EUV ux involves a complex physical process of primary (photons) and secondary (electrons) interactions. It relies on cross-section libraries and tabulated distribution functions for secondary particle production and energy losses, implemented in the MCNP6 general-purpose Monte Carlo solution, and utilized in our coupled photon-electron transport calculations. The solution takes into account all fundamental photoand electro-atomic transport processes, including sub-shell electro-ionization that affects the atomic relaxation process for energies down to one eV. The most signicant improvement is made by including all atomic electron subshells that affect the atomic relaxation process for these energies. Data structures include subshell binding energies, ground-state electron populations, and the number of possible relaxation transitions. Photon transport enhancements are based on a new dataset specic to atomic subshells and incorporated into MCNP6, and completion of form factor data for coherent and incoherent scattering. These results will be applied to ionospheric electron temperature measurements from Langmuir probes on board the European Space Agency’s Swarm satellite mission.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".