A Study of the Electronic and Ionic Structure, for Competing States of Fully and Partially Ionized Hydrogen, Using the Neutral Pseudo‐Atom Method as Well as a Classical Map for the Electron Subsystem
Bibliographic record
Abstract
ABSTRACT Prof. Bonitz and his collaborators have made seminal contributions to the study of the uniform electron fluid and the electron‐proton fluid, viz., hydrogen, in using ab initio simulations. as reflected in this festschrift. Here we review the theoretical methods available for these systems where traditional small‐parameter methods fail. We use the neutral‐pseudo atom (NPA) method, and a classical map for quantum electrons to study hydrogen plasmas. We show that both fully‐ionized and partially‐ionized hydrogen phases can exist with the same nominal density and temperature, at pressures and temperatures of interest to planetary physics. The mean ionization , pair‐distribution functions, free energies, pressures and conductivities are calculated for the competing phases. Here is also a measure of the miscibility of fully ionized and un‐ionized hydrogen. Recent studies using path‐integral Monte Carlo methods, and ‐atom Density Functional Theory (DFT) simulations have provided essential structure data including the electron–electron structure factor that enters into interpretation of x‐ray Thomson scattering and other diagnostics. We show that these structure data can be inexpensively evaluated using classical‐map schemes for fully ionized plasmas, and more generally, using one‐atom (average‐atom) DFT methods for partially ionized systems.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".