Dynamics, nucleosynthesis, and kilonova signature of black hole—neutron star merger ejecta
Bibliographic record
Abstract
Abstract We investigate the ejecta from black hole—neutron star mergers by modeling the formation and interaction of mass ejected in a tidal tail and a disk wind. The outflows are neutron-rich, giving rise to optical/infrared emission powered by the radioactive decay of r -process elements (a kilonova ). Here we perform an end-to-end study of this phenomenon, where we start from the output of a fully-relativistic merger simulation, calculate the post-merger hydrodynamical evolution of the ejecta and disk winds including neutrino physics, determine the final nucleosynthetic yields using post-processing nuclear reaction network calculations, and compute the kilonova emission with a radiative transfer code. We study the effects of the tail-to-disk mass ratio by scaling the tail density. A larger initial tail mass results in fallback matter becoming mixed into the disk and ejected in the subsequent disk wind. Relative to the case of a disk without dynamical ejecta, the combined outflow has lower mean electron fraction, faster speed, larger total mass, and larger absolute mass free of high-opacity Lanthanides or Actinides. In most cases, the nucleosynthetic yield is dominated by the heavy r -process contribution from the unbound part of the dynamical ejecta. A Solar-like abundance distribution can however be obtained when the total mass of the dynamical ejecta is comparable to the mass of the disk outflows. The kilonova has a characteristic duration of 1 week and a luminosity of ∼ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mstyle displaystyle="false"> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mn>41</mml:mn> </mml:mrow> </mml:msup> </mml:mstyle> </mml:math> erg <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mstyle displaystyle="false"> <mml:msup> <mml:mrow> <mml:mi mathvariant="normal">s</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:mstyle> </mml:math> , with orientation effects leading to variations of a factor ∼2 in brightness. At early times ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mstyle displaystyle="false"> <mml:mo><</mml:mo> </mml:mstyle> </mml:math> 1 d) the emission includes an optical component from the (hot) Lanthanide-rich material, but the spectrum evolves quickly to the infrared thereafter.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".