Searching for string bosenovas with gravitational wave detectors
Bibliographic record
Abstract
A bstract We study the phenomenology of a string bosenova explosion in vector superradiance clouds around spinning black holes, focusing on the observable consequences in gravitational wave detectors and accelerometers. During the superradiance growth of a dark photon cloud — which occurs for dark photon masses $$ {m}_{A^{\prime }}\sim {10}^{-14}-{10}^{-11}\textrm{eV} $$ m A ′ ~ 10 − 14 − 10 − 11 eV around stellar-mass black holes ( $$ {m}_{A^{\prime }}\sim {10}^{-23}-{10}^{-16}\textrm{eV} $$ m A ′ ~ 10 − 23 − 10 − 16 eV for supermassive black holes) — the dark electromagnetic field might reach a critical field strength, when a network of dark photon strings is produced via a superheated phase transition. These dark photon strings will then absorb the energy in the background gauge fields and get ejected from the cloud, with total energy of the string network as large as the total rotational energy of the spinning black hole. In this paper, we study the subsequent evolution of this dense string network, and the resulting observational consequences depending on the unknown string tension, or almost equivalently, the ratio between the quartic and the gauge coupling in the Abelian Higgs model. Strings with large tension will dissipate into gravitational waves, detectable over a wide range of frequencies, from ~ nHz near supermassive blackholes, to ≳ 10MHz around stellar mass black holes. This is the first known source of high frequency gravitational waves, unconstrained by cosmological observations. The strain of this gravitational wave can be larger than 10 −14 at low frequencies, lasting for longer than typical duration of experiments. Small tension strings, whose string networks can have total lengths as large as 10 40 km, can travel to the earth with appreciable rate from any black hole in the Milky Way and interact with earth based accelerometers. If the Standard Model particles are directly charged under the dark photon, e.g. U(1) B−L , this interaction leads to an acceleration of Standard Model particles that is independent of the coupling strength. We work out the spectral density of this acceleration, and project that modern accelerometers and equivalence principle tests can be sensitive to the passing of these strings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".