Calculating the Hawking temperature of black holes in <i>f</i>(<i>Q</i>) gravity using the RVB method: a residue-based approach
Bibliographic record
Abstract
This paper explores the computation of Hawking temperatures for black holes within various f( Q) gravity models using the RVB (Robson–Villari–Biancalana) method. This topological approach reveals an additional term in the temperature calculation, which we propose is a residue arising from the contour integral [Formula: see text], where f( z) represents a function related to the black hole’s metric or curvature. By analyzing several specific f( Q) models including f( Q) = Q + α Q 2 , f( Q) = Q + βln ( Q), [Formula: see text], f( Q) = Q n as well as the Reissner–Nordstrm, Kerr, and Kerr–Newman black holes, we demonstrate that the correction term C can be consistently interpreted as this residue, providing new insights into black hole thermodynamics in modified gravity frameworks. We also expand on important physical aspects such as black hole stability, late-stage evaporation, extremality bounds in charged and rotating spacetimes, and potential novel phases emerging from different forms of f( Q).
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".