Geometric and topological properties of marginally outer trapped surfaces
Bibliographic record
Abstract
The modern theory of gravity was introduced by Albert Einstein in 1915. In General Relativity there is a one-to-one relationship between geometry and gravity. Black holes are one of the most interesting predictions of general relativity. The Schwarzschild solution or Schwarzschild black hole is named in honor of Karl Schwarzschild, who found this exact solution in 1915 and published it in January 1916. It was the first exact solution of the Einstein field equations other than the trivial flat space solution. Since then black holes have become an important as well as interesting part of GR. In the early days of general relativity, nobody believed that black holes actually exist. However observational evidence of their existence is now overwhelming [13, 1]. One definition of black holes which is very common is that a black hole is a region of spacetime from which even light cannot escape. But this global definition is not very useful for understanding the dynamics of black holes. In this thesis, we want to answer these questions: how can we define a black hole locally? And how can that definition be used to better understand things like black hole mergers? We begin with the definition of a marginal outer trapped surface (MOTS) and then we will discuss what we know about them and what is our goal for the future.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".