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Preprint . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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Lecture 2- Modular Representations and Brauer Characters

Authors: Chuang, William Huanshan;

Lecture 2- Modular Representations and Brauer Characters

Abstract

Introduces modular systems (K, O, k), defines p-regular vs p-singular elements, and develops Brauer characters (defined on p-regular classes) with the Brauer–Nesbitt theorem. Explains reduction mod p, the decomposition matrix D linking ordinary and Brauer characters, and that the number of Brauer irreducibles equals the number of p-regular conjugacy classes. Worked examples include S₃ at p=3 and the kernel phenomenon in passing from ordinary to modular characters; a preview points to Frobenius actions and field-of-definition issues next.

Portions of editing assistance were provided by OpenAI ChatGPT. All content was reviewed and verified by the author.

Keywords

reduction mod p, modular representation theory, kernel/nullspace, p-regular/p-singular, S₃ example, Brauer characters, decomposition matrix, Brauer–Nesbitt

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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