Multimessenger asteroseismology of core-collapse supernovae
Bibliographic record
Abstract
We investigate correlated gravitational wave and neutrino signals from rotating core-collapse supernovae with simulations. Using an improved mode identification procedure based on mode function matching, we show that a linear quadrupolar mode of the core produces a dual imprint on gravitational waves and neutrinos in the early post-bounce phase of the supernova. The angular harmonics of the neutrino emission are consistent with the mode energy around the neutrinospheres, which points to a mechanism for the imprint on neutrinos. Thus, neutrinos carry information about the mode amplitude in the outer region of the core, whereas gravitational waves probe deeper in. We also find that the best-fit mode function has a frequency bounded above by $\ensuremath{\sim}420\text{ }\text{ }\mathrm{Hz}$, and yet the mode's frequency in our simulations is $\ensuremath{\sim}15%$ higher, due to the use of Newtonian hydrodynamics and a widely used pseudo-Newtonian gravity approximation. This overestimation is particularly important for the analysis of gravitational wave detectability and asteroseismology, pointing to limitations of pseudo-Newtonian approaches for these purposes, possibly even resulting in excitation of incorrect modes. In addition, mode frequency matching (as opposed to mode function matching) could be resulting in mode misidentification in recent work. Lastly, we evaluate the prospects of a multimessenger detection of the mode using current technology. The detection of the imprint on neutrinos is most challenging, with a maximum detection distance of $\ensuremath{\sim}1\text{ }\text{ }\mathrm{kpc}$ using the IceCube Neutrino Observatory. The maximum distance for detecting the complementary gravitational wave imprint is $\ensuremath{\sim}5\text{ }\text{ }\mathrm{kpc}$ using Advanced LIGO at design sensitivity.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".