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Record W2237821232 · doi:10.2140/pjm.2015.279.155

Essential dimension and error-correcting codes

2015· article· en· W2237821232 on OpenAlexaff
Shane Cernele, Zinovy Reichstein

Bibliographic record

VenuePacific Journal of Mathematics · 2015
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMathematicsDimension (graph theory)Pure mathematics

Abstract

fetched live from OpenAlex

One of the important open problems in the theory of central simple algebras is to compute the essential dimension of GL n = m , i.e., the essential dimension of a generic division algebra of degree n and exponent dividing m.In this paper we study the essential dimension of groups of the formwhere C is a central subgroup of GL n 1 GL n r .Equivalently, we are interested in the essential dimension of a generic r-tuple .A 1 ; : : : ; A r / of central simple algebras such that deg.A i / D n i and the Brauer classes of A 1 ; : : : ; A r satisfy a system of homogeneous linear equations in the Brauer group.The equations depend on the choice of C via the error-correcting code Code.C / which we naturally associate to C .We focus on the case where n 1 ; : : : ; n r are powers of the same prime.The upper and lower bounds on ed.G / we obtain are expressed in terms of coding-theoretic parameters of Code.C /, such as its weight distribution.Surprisingly, for many groups of the above form the essential dimension becomes easier to estimate when r 3; in some cases we even compute the exact value.The Appendix by Athena Nguyen contains an explicit description of the Galois cohomology of groups of the form .GL n 1 GL n r /=C .This description and its corollaries are used throughout the paper.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.029
GPT teacher head0.261
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2015
Admission routes1
Has abstractyes

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Same venuePacific Journal of MathematicsSame topicCoding theory and cryptographyFrench-language works237,207