Mapping the likelihood of GW190521 with diverse mass and spin priors
Bibliographic record
Abstract
We map the likelihood of GW190521, the heaviest detected binary black hole (BBH) merger, by sampling under different mass and spin priors designed to be uninformative. We find that a source-frame total mass of $\ensuremath{\sim}150\text{ }\text{ }{M}_{\ensuremath{\bigodot}}$ is consistently supported, but posteriors in mass ratio and spin depend critically on the choice of priors. We confirm that the likelihood has a multimodal structure with peaks in regions of mass ratio representing very different astrophysical scenarios. The unequal-mass region (${m}_{2}/{m}_{1}<0.3$) has an average likelihood $\ensuremath{\sim}{e}^{6}$ times larger than the equal-mass region (${m}_{2}/{m}_{1}>0.3$) and a maximum likelihood $\ensuremath{\sim}{e}^{2}$ larger. Using ensembles of samples across priors, we examine the implications of qualitatively different BBH sources that fit the data. We find that the equal-mass solution has poorly constrained spins and at least one black hole mass that is difficult to form via stellar collapse due to pair instability. The unequal-mass solution can avoid this mass gap entirely but requires a negative effective spin and a precessing primary. Either of these scenarios is more easily produced by dynamical formation channels than field binary coevolution. Drawing representative samples from each region of the likelihood map, we find a sensitive comoving volume time $\mathcal{O}(10)$ times larger in the mass gap region than the gap-avoiding region. Considering ${D}_{\mathrm{com}}^{3}\mathcal{L}$ to account for the distance effect, the likelihood of these representative samples still reverses the advantage to favor the gap-avoiding scenario by a factor of $\mathcal{O}(100)$ before including mass and spin priors. Posteriors are easily driven away from this high-likelihood region by common prior choices meant to be uninformative, making GW190521 parameter inference sensitive to the assumed mass and spin distributions of mergers in the source's astrophysical channel. This may be a generic issue for similarly heavy events given current detector sensitivity and waveform degeneracies.
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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 | 0.003 | 0.013 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".