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5d to 3d compactifications and discrete anomalies

Abstract:
Much insight into the dynamics of quantum field theories can be gained by studying the relationship between field theories in different dimensions. An interesting observation is that when two theories are related by dimensional reduction on a compact surface, their ’t Hooft anomalies corresponding to continuous symmetries are also related: the anomaly polynomial of the lower-dimensional theory can be obtained by integrating that of the higher-dimensional one on the compact surface. Naturally, this relation only holds if both theories are even dimensional. This raises the question of whether similar relations can also hold for the case of anomalies in discrete symmetries, which might be true even in odd dimensions. The natural generalization to discrete symmetries is that the anomaly theories, associated with the lower and higher dimensional theories, would be related by reduction on the compact surface. We explore this idea for compactifications of 5d superconformal field theories (SCFTs) to 3d on Riemann surfaces with global-symmetry fluxes. In this context, it can be used both as a check for these compactification constructions and for discovering new anomalies in the 5d SCFTs. This opens the way to applying the same idea of dimensional reduction of the anomaly theory to more general types of compactifications.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/jhep10(2023)185

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
ORCID:
0000-0003-0316-3369


Publisher:
Springer
Journal:
Journal of High Energy Physics More from this journal
Volume:
2023
Issue:
10
Pages:
185
Article number:
185
Publication date:
2023-10-30
Acceptance date:
2023-10-16
DOI:
EISSN:
1029-8479
ISSN:
1126-6708


Language:
English
Keywords:
Pubs id:
1827484
UUID:
uuid_c9b58d42-0a93-491b-beb5-71a10c868280
Local pid:
pubs:1827484
Source identifiers:
3735731
Deposit date:
2026-02-06
ARK identifier:
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