Multitrace deformation of the Aharony-Bergman-Jafferis-Maldacena theory
Bibliographic record
Abstract
Motivated by the study of big crunch singularities in asymptotically ${\mathrm{AdS}}_{4}$ space-times, we consider a marginal triple trace deformation of Aharony-Bergman-Jafferis-Maldacena (ABJM) theory. The deformation corresponds to adding a potential which is unbounded below. In a 't Hooft large $N$ limit, the beta function for the triple trace deformation vanishes, which is consistent with the near-boundary behavior of the bulk fields. At the next order in the $1/N$ expansion, the triple trace couplings exhibit nontrivial running, which we analyze explicitly in the limit of zero 't Hooft coupling, in which the model reduces to an $O(N)\ifmmode\times\else\texttimes\fi{}O(N)$ vector model with large $N$. In this limit, we establish the existence of a perturbative UV fixed point, and we comment on possible nonperturbative effects. We also show that the bulk analysis leading to big crunch singularities extends to the ${\mathbb{Z}}_{k}$ orbifold models dual to ABJM theory.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".