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Record W3186767008 · doi:10.82308/27266

Intersections of closed geodesics on Shimura curves

2021· article· en· W3186767008 on OpenAlexfundno aff
James Rickards

Bibliographic record

VenueeScholarship@McGill (McGill) · 2021
Typearticle
Languageen
FieldMathematics
TopicGeometric Analysis and Curvature Flows
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsGeodesicGeologyGeodesyMathematicsGeometry

Abstract

fetched live from OpenAlex

Let G be a discrete subgroup of PSL(2, R), and consider closed geodesics on the quotient of the upper half plane by G. In this thesis, we study how these geodesics intersect when G is the group of units of norm 1 in an Eichler order of an indefinite quaternion algebra over Q, i.e. over a Shimura curve. We start by developing some theory for a general G, providing a pathway to interpret the geometry of the situation (intersection point, angle, etc.) in terms of the algebra of G. The next focus is on G=PSL(2, Z), where we relate the work to Conway's topograph, as well as work by Duke, Imamoglu, and Toth on the linking number of modular knots. We then detail some background on quaternion algebras, before diving in to the Shimura curve case. We re-interpret intersection numbers in terms of x-linking of optimal embeddings of real quadratic orders, and produce formulas which count the total amount of x-linking in a given Eichler order. These formulas are essentially a real quadratic analogue to classical results of Gross and Zagier. We define Hecke operators acting on optimal embeddings, and using the signed intersection pairing, produce formal q-series, which are proven to be weight two modular forms on Gamma_0(N). The thesis is concluded with a conjectural relation to work of Darmon and Vonk on a real quadratic analogue to the difference of j-values, a brief description of the practical algorithms used to compute with intersection numbers, and a short survey of future projects

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 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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.353
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.275
Teacher spread0.233 · 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 teacher head, not a consensus.

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

Citations6
Published2021
Admission routes1
Has abstractyes

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