’t Hooft anomalies and the holomorphy of supersymmetric partition functions
Bibliographic record
Abstract
Abstract We study the dependence of supersymmetric partition functions on continuous parameters for the flavor symmetry group, G F , for 2d $$ \mathcal{N} $$ N = (0, 2) and 4d $$ \mathcal{N} $$ N = 1 supersymmetric quantum field theories. In any diffeomorphism-invariant scheme and in the presence of G F ’t Hooft anomalies, the supersymmetric Ward identities imply that the partition function has a non-holomorphic dependence on the flavor parameters. We show this explicitly for the 2d torus partition function, $$ {Z}_{T^2} $$ Z T 2 , and for a large class of 4d partition functions on half-BPS four-manifolds, $$ {Z}_{{\mathcal{M}}^4} $$ Z M 4 — in particular, for $$ \mathcal{M} $$ M 4 = S 3 × S 1 and $$ \mathcal{M} $$ M 4 = Σ g × T 2. We propose a new expression for $$ {Z}_{{\mathcal{M}}_{d-1}\times {S}^1} $$ Z M d − 1 × S 1 , which differs from earlier holomorphic results by the introduction of a non-holomorphic “Casimir” pre-factor. The latter is fixed by studying the “high temperature” limit of the partition function. Our proposal agrees with the supersymmetric Ward identities, and with explicit calculations of the absolute value of the partition function using a gauge-invariant zeta-function regularization.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".