Multidimensional classical and relativistic hydrodynamics using central and WENO schemes
Bibliographic record
Abstract
The effects of density fluctuations on supernova neutrinos have been studied. Using the formalism developed by Burgess & Michaud (BM) and stellar evolution progenitors by Woosley & Weaver, the expected neutrino flux from a future galactic super-nova have been computed taking into account possible density fluctuations for a 2ν system. It has been shown that within the most recent constraints of mass squared difference values and vacuum mixing angle, neutrino fluxes on earth could be affected depending on the fluctuation levels. The formalism developed by BM has been extended to the case of three neutrino generations. Preliminary results using this model show that in this case as well, density fluctuations could affect the expected neutrino flux. A new multidimensional, non-Riemann solver based, High resolution Shock Capturing (HRSC) scheme has been proposed using the semidiscrete central and Weighted Essentially Non-Oscillatory (WENO) data reconstruction methods. The novel aspect of this algorithm is that for robustness, elements of the Piecewise Parabolic Method (PPM) has been incorporated in this HRSC scheme. The algorithm has been applied to the multidimensional classical and Special Relativistic Hydrodynamics (SRHD) equations. The new HRSC algorithm and codes were verified by a number of benchmark tests in one and two dimensions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".