Marginally outer trapped (open) surfaces in 4+1 dimensional spacetimes
Bibliographic record
Abstract
Home>Marginally outer trapped (open) surfaces in 4+1 dimensional spacetimes Marginally outer trapped (open) surfaces in 4+1 dimensional spacetimes MacDonald Muth, Sara Mime (2021) Marginally outer trapped (open) surfaces in 4+1 dimensional spacetimes. Masters thesis, Memorial University of Newfoundland. [img] [English] PDF - Accepted Version Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. Download (4MB) Abstract In binary black hole mergers and other highly dynamical spacetimes, the surface of most obvious interest, the event horizon, is often computationally difficult to locate. Instead, it is useful to use quasi-local characterizations of black hole boundaries, such as Marginally Outer Trapped Surfaces (MOTS), the outer-most of which is (often) the apparent horizon. Recent studies have shown that MOTS not only characterize boundaries, but may also be found in black hole interiors. This has been seen in 4D Schwarzschild and Reissner-Nordstrom, as well as in binary black hole mergers. In this thesis, behaviours of MOTS|and their open generalization, Marginally Outer Trapped Open Surfaces (MOTOS)|in the interior of five-dimensional black holes are studied; both static (Schwarzschild), and rotating (Myers-Perry). Similar to four-dimensions, we find infinitely many self-intersecting MOTS in 5D Schwarzschild. We find finitely many self-intersecting MOTS in Myers-Perry, finding fewer as the rotation increases. However, we do find oscillations of the MOTOS, which is novel behaviour.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".