Lyα RADIATIVE TRANSFER IN COSMOLOGICAL SIMULATIONS USING ADAPTIVE MESH REFINEMENT
Bibliographic record
Abstract
A numerical code for solving various Lyα radiative transfer (RT) problems is presented. The code is suitable for an arbitrary, three-dimensional distribution of Lyα emissivity, gas temperature, density, and velocity field. Capable of handling Lyα RT in an adaptively refined grid-based structure, it enables detailed investigation of the effects of clumpiness of the interstellar (or intergalactic) medium. The code is tested against various geometrically and physically idealized configurations for which analytical solutions exist, and subsequently applied to three different simulated high-resolution "Lyman-break galaxies," extracted from high-resolution cosmological simulations at redshift z = 3.6. Proper treatment of the Lyα scattering reveals a diversity of surface brightness (SB) and line profiles. Specifically, for a given galaxy the maximum observed SB can vary by an order of magnitude, and the total flux by a factor of 3–6, depending on the viewing angle. This may provide an explanation for differences in observed properties of high-redshift galaxies, and in particular a possible physical link between Lyman-break galaxies and regular Lyα emitters.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".