Stochastic and Resolvable Gravitational Waves from Ultralight Bosons
Bibliographic record
Abstract
Ultralight scalar fields around spinning black holes can trigger superradiant instabilities, forming a long-lived bosonic condensate outside the horizon. We use numerical solutions of the perturbed field equations and astrophysical models of massive and stellar-mass black hole populations to compute, for the first time, the stochastic gravitational-wave background from these sources. In optimistic scenarios the background is observable by Advanced LIGO and LISA for field masses ${m}_{s}$ in the range $\ensuremath{\sim}[2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}13},{10}^{\ensuremath{-}12}]$ and $\ensuremath{\sim}5\ifmmode\times\else\texttimes\fi{}[{10}^{\ensuremath{-}19},{10}^{\ensuremath{-}16}]\text{ }\text{ }\mathrm{eV}$, respectively, and it can affect the detectability of resolvable sources. Our estimates suggest that an analysis of the stochastic background limits from LIGO O1 might already be used to marginally exclude axions with mass $\ensuremath{\sim}{10}^{\ensuremath{-}12.5}\text{ }\text{ }\mathrm{eV}$. Semicoherent searches with Advanced LIGO (LISA) should detect $\ensuremath{\sim}15(5)$ to 200(40) resolvable sources for scalar field masses $3\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}13}$ $({10}^{\ensuremath{-}17})\text{ }\mathrm{eV}$. LISA measurements of massive BH spins could either rule out bosons in the range $\ensuremath{\sim}[{10}^{\ensuremath{-}18},2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}13}]\text{ }\text{ }\mathrm{eV}$, or measure ${m}_{s}$ with 10% accuracy in the range $\ensuremath{\sim}[{10}^{\ensuremath{-}17},{10}^{\ensuremath{-}13}]\text{ }\text{ }\mathrm{eV}$.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".