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On Minimal Length Factorizations of Finite Groups

2003· article· en· W1983860602 on OpenAlexaff
María Isabel González Vasco, Martin Rötteler, Rainer Steinwandt

Bibliographic record

VenueExperimental Mathematics · 2003
Typearticle
Languageen
FieldMathematics
TopicFinite Group Theory Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMathematicsLogarithmDiscrete logarithmGroup (periodic table)Simple (philosophy)ComputationSimple groupFinite groupCryptographyOrder (exchange)Signature (topology)CombinatoricsDiscrete mathematicsPure mathematicsAlgorithmComputer sciencePublic-key cryptographyMathematical analysisGeometryEncryption

Abstract

fetched live from OpenAlex

Logarithmic signaturesare a special type of group factorizations, introduced as basic components of certain cryptographic keys. Thus, short logarithmic signatures are of special interest. We deal with the question of finding logarithmic signatures of minimal length in finite groups. In particular, such factorizations exist for solvable, symmetric, and alternating groups. We show how to use the known examples to derive minimal length logarithmic signatures for other groups. Namely, we prove the existence of such factorizations for several classical groups and—in parts by direct computation—for all groups of order <175560 (= ord(J 1), where J 1 is Janko's first sporadic simple group). Whether there exists a minimal length logarithmic signature for each finite group still remains an open question.

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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0020.006
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.083
GPT teacher head0.360
Teacher spread0.278 · 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

Citations26
Published2003
Admission routes1
Has abstractyes

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