Cardy limit of the 3d superconformal index
Bibliographic record
Abstract
We study the superconformal index $Z(q)$ of 3d $\mathcal{N}=2$ gauge theories in Cardy-like limits $β= \log \tfrac{1}{q} \to 0^+$, extending techniques recently developed in the 4d $\mathcal{N}=1$ context. For theories with vectorlike matter content we find on the first sheet ($q \to 1$) that $Z(q) \sim β^{-\#}$, where the exponent $\#$ is determined by a $multiscale\ decomposition$ of the BPS moduli space appearing in the localization formula for the index. On the second sheet ($q \to e^{2πi})$ we find $Z(q) \sim e^{\#/ β}$, and that the long-standing puzzle of apparent gauge-enhancing saddles is resolved (in the absence of Chern--Simons couplings) via a novel $Lorentzian\ factorization$ formula that establishes complete screening. A key insight is the use of $Poisson\ resummation$, which streamlines the asymptotic analysis, sharpens the link to Kaluza--Klein effective field theory, and provides a dual description of parts of the BPS moduli space in terms of punctured surfaces. The Lorentzian factorization formula also emerges from Poisson resummation, though applied after a contour crossing in moduli space. This, in turn, hints at a correspondence between 3d monopoles and vortices via 2d duality.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".