Bibliographic record
Abstract
In this talk I give a status report on a project in which we try to combine the usual D3–brane inflationary scenario in a warped throat ge-ometry a la KKLMMT with D3/D7–brane inflation. The latter relies on non–supersymmetric flux on the D7–brane worldvolume to create an attractive force between the otherwise stable (because respectively susy) D–branes. This is work in progress with Keshav Dasgupta, Paul Franche and James Sully (McGill). 1 Motivation and basic idea Today’s D–brane inflation models (e.g. [1, 2, 3, 4]) are usually embedded in a type IIB string theory setup, which has become known as the “warped throat”. It is a background on which fluxes create a strongly warped Calabi–Yau ge-ometry via their backreaction on the metric. The Calabi–Yau in question is taken to be a conifold, because it is the only Calabi–Yau of which we explicitly know the metric (also orbifolds of tori have proved useful for model building). The only problem with this CY is that it is non–compact. In order to have a sensible 4–dimensional theory, one needs to compactify this setup, which is done by gluing the throat to a compact bulk. This bulk is some non–specified 6–dimensional Calabi–Yau, which must generically contain orientifold planes, wrapped D–branes and fluxes (other than those in the throat) to consistently cancel all charges, see e.g. [5] for a description of this model. It is illustrated in figure 1. The role of the inflaton is played by the distance of the D3–brane from the tip of the throat, where usually an anti–D3 is placed. Because this anti–D3 1
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".