Search for long-transient gravitational waves from ultralight vector boson clouds
Bibliographic record
Abstract
Ultralight bosons are predicted in many extensions of the Standard Model and may make up a significant fraction of dark matter. Through the superradiance process, they can extract energy from rotating black holes, forming macroscopic clouds that emit quasi-continuous gravitational waves. Probing these signatures with gravitational wave detectors provides us with a unique opportunity to explore beyond-Standard Model physics that is out of reach for terrestrial experiments. This thesis presents the design and implementation of a search pipeline to detect gravitational waves from ultralight vector boson clouds around binary merger remnant black holes observed by the Advanced LIGO, Virgo, and KAGRA (LVK) observatories. The search method incorporates a hidden Markov model that is able to efficiently track the frequency evolution of these long-transient signals. We simulate the signal waveforms with high accuracy using the numerical relativity modeling tool Superrad. Sensitivity studies demonstrate that the search method can detect signals from sources out to ~1 Gpc in parts of the parameter space. To address the various challenges associated with signal candidate follow-up and noise rejection, this thesis also investigates two Doppler-based veto procedures and proposes an effective point spread function be used to differentiate signals from noise. This is later used to quantify the tolerance of the search to sky position mismatch for different targets. In the absence of a detection, a statistically rigorous framework is introduced to constrain the existence of the vector boson mass while marginalizing over uncertainties in the black hole parameters. It is also shown how these constraints can be extended to accommodate additional bosonic interactions. Finally, combining the search pipeline and follow-up studies, we carry out the first directed search for gravitational waves from ultralight vector boson clouds around two remnant black holes detected during the LVK's fourth observing run. No evidence of a signal is found, so constraints are derived on the corresponding vector mass ranges. The results demonstrate that current-generation detectors are fast approaching the required sensitivity to derive physically meaningful exclusions on the vector boson mass. Moreover, this thesis lays the foundation for more sensitive searches in future observing runs and with next-generation gravitational wave detectors.
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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 | 0.002 |
| 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".