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Record W2616191523 · doi:10.46298/dmtcs.2424

A simple recurrence formula for the number of rooted maps on surfaces by edges and genus

2014· article· en· W2616191523 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDiscrete Mathematics & Theoretical Computer Science · 2014
Typearticle
Languageen
FieldMathematics
TopicAdvanced Combinatorial Mathematics
Canadian institutionsUniversity of Waterloo
FundersAgence Nationale de la Recherche
KeywordsCombinatoricsBijectionMathematicsSimple (philosophy)GenusBipartite graphInterpretation (philosophy)Generating functionPhilosophy

Abstract

fetched live from OpenAlex

We establish a simple recurrence formula for the number $Q_g^n$ of rooted orientable maps counted by edges and genus. The formula is a consequence of the KP equation for the generating function of bipartite maps, coupled with a Tutte equation, and it was apparently unnoticed before. It gives by far the fastest known way of computing these numbers, or the fixed-genus generating functions, especially for large $g$. The formula is similar in look to the one discovered by Goulden and Jackson for triangulations (although the latter does not rely on an additional Tutte equation). Both of them have a very combinatorial flavour, but finding a bijective interpretation is currently unsolved - should such an interpretation exist, the history of bijective methods for maps would tend to show that the case treated here is easier to start with than the one of triangulations. Nous établissons une formule de récurrence simple pour le nombre $Q_g^n$ de cartes enracinées de genre $g$ à $n$ arêtes. Cette formule est une conséquence relativement simple du fait que la série génératrice des cartes biparties est une solution de l’équation KP et d’une équation de Tutte, et elle était apparemment passée inaperçue jusque là. Elle donne de loin le moyen le plus rapide pour calculer ces nombres, en particulier quand $g$est grand. La formule est d’apparence similaire à celle découverte par Goulden et Jackson pour les triangulations (quoique cette dernière ne repose pas sur une équation de Tutte additionnelle). Les deux formules ont une saveur très combinatoire, mais trouver une interprétation bijective reste un problème ouvert – mais si une telle interprétation existe, l’histoire des méthodes bijectives pour les cartes tendrait à montrer que le cas traité ici est plus facile pour commencer que celui des triangulations.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.311
Teacher spread0.290 · 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