Black hole superradiance signatures of ultralight vectors
Bibliographic record
Abstract
The process of superradiance can extract angular momentum and energy from astrophysical black holes (BHs) to populate gravitationally bound states with an exponentially large number of light bosons. We analytically calculate superradiant growth rates for vectors around rotating BHs in the regime where the vector Compton wavelength is much larger than the BH size. Spin-1 bound states have superradiance times as short as a second around stellar BHs, growing up to a thousand times faster than their spin-0 counterparts. The fast rates allow us to use measurements of rapidly spinning BHs in x-ray binaries to exclude a wide range of masses for weakly coupled spin-1 particles, $5\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}14}\ensuremath{-}2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}11}\text{ }\text{ }\mathrm{eV}$; lighter masses in the range $6\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}20}\ensuremath{-}2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}17}\text{ }\text{ }\mathrm{eV}$ start to be constrained by supermassive BH spin measurements at a lower level of confidence. We also explore routes to detection of new vector particles possible with the advent of gravitational wave (GW) astronomy. The LIGO-Virgo Collaboration could discover hints of a new light vector particle in statistical analyses of masses and spins of merging BHs. Vector annihilations source continuous monochromatic gravitational radiation which could be observed by current GW observatories. At design sensitivity, Advanced LIGO may measure up to thousands of annihilation signals from within the Milky Way, while hundreds of BHs born in binary mergers across the observable Universe may superradiate vector bound states and become new beacons of monochromatic gravitational waves.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".