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Record W1810220960 · doi:10.1090/tran/6829

Quadratic equations in hyperbolic groups are NP-complete

2015· preprint· en· W1810220960 on OpenAlexaff
Olga Kharlampovich, Atefeh Mohajeri, Alex Taam, Alina Vdovina

Bibliographic record

VenueTransactions of the American Mathematical Society · 2015
Typepreprint
Languageen
FieldMathematics
TopicGeometric and Algebraic Topology
Canadian institutionsMcGill University
FundersEngineering and Physical Sciences Research CouncilNational Science Foundation
KeywordsMathematicsQuadratic equationBounded functionConstant (computer programming)Torsion (gastropod)Upper and lower boundsVariable (mathematics)Mathematical analysisCombinatoricsGeometry

Abstract

fetched live from OpenAlex

We prove that in a torsion-free hyperbolic group Γ \Gamma , the length of the value of each variable in a minimal solution of a quadratic equation Q = 1 Q=1 is bounded by N | Q | 3 N|Q|^3 for an orientable equation, and by N | Q | 4 N|Q|^{4} for a non-orientable equation, where | Q | |Q| is the length of the equation and the constant N N can be computed. We show that the problem, whether a quadratic equation in Γ \Gamma has a solution, is in NP, and that there is a PSpace algorithm for solving arbitrary equations in Γ \Gamma . If additionally Γ \Gamma is non-cyclic, then this problem (of deciding existence of a solution) is NP-complete. We also give a slightly larger bound for minimal solutions of quadratic equations in a toral relatively hyperbolic group.

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)0.007
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 score0.024
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.007
Open science0.0020.003
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0240.004

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 head0.081
GPT teacher head0.324
Teacher spread0.243 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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