The Burn-UD code for the numerical simulations of the Hadronic-to-Quark-Matter phase transition
Bibliographic record
Abstract
Burn-UD is a hydrodynamic combustion code used to model the phase transition of hadronic to quark matter with particular application to the interior of neutron stars. Burn-UD models the flame micro-physics for different equations of state (EoS) on both sides of the interface, i.e. for both the ash (up-down-strange quark phase) and the fuel (up-down quark phase). It also allows the user to explore strange quark seeding produced by different processes including DM annihilation inside neutron stars. The simulations provide a physical window to diagnose whether the combustion process will simmer quietly and slowly, lead to a transition from deflagration to detonation or a (quark) core-collapse explosion. Such an energetic phase transition (a Quark-Nova) would have consequences in high-energy astrophysics and could aid in our understanding of many still enigmatic astrophysical transients. Furthermore, having a precise understanding of the phase transition dynamics for different EoSs could aid further in constraining the nature of the non-perturbative regimes of QCD in general. We hope that Burn-UD will evolve into a platform/software to be used and shared by the QCD community exploring the phases of Quark Matter and astrophysicists working on Compact Stars.
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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 | 0.001 |
| 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 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".