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Record W7132936686

Lattice Point Counts in Teichmuller Space and Negative Curvature

2023· dissertation· W7132936686 on OpenAlexaff
Pouya Honaryar

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldMathematics
TopicGeometric Analysis and Curvature Flows
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBall (mathematics)Bounded functionCurvatureTeichmüller spaceManifold (fluid mechanics)Lattice (music)Covering spaceHomeomorphism (graph theory)Differential geometry
DOInot available

Abstract

fetched live from OpenAlex

In this thesis we present two different, but related, results; one in the setting of Teichmuller theory, and the other in the setting of negative curvature. For the first result, let $\gamma$ be a pseudo-Anosov homeomorphism of a compact orientable surface $S_g$, and let $L_\gamma$ denote the axis of the action of $\gamma$ on the Teichmuller space of $S_g$, denoted by $\mathcal{T}_g$. In Chapter 3 we obtain asymptotics for the number of translates of $L_\gamma$ that intersect a Teichmuller ball of radius $R$ centered at a fixed $X \in \mathcal{T}_g$, as $R \rightarrow \infty$. For the second result, let $M$ be a compact closed manifold of variable negative curvature. We fix two points $x, y$ in the universal cover $\widetilde{M}$ of $M$, fix an element $\mathrm{id} \neq \gamma$ in the fundamental group $\Gamma$ of $M$, and denote the set of elements in $\Gamma$ that are conjugate to $\gamma$ by $\mathrm{Conj}_\gamma$. In Chapter 4 we obtain asymptotics for the number of $\mathrm{Conj}_\gamma$--orbits of $y$ that lie in a ball of radius $R$ centered at $x$, as $R \rightarrow \infty$. If $M$ is two-dimensional, or of dimension $n \geq 3$ and curvature bounded above by $-1$ and below by $-(\frac{n-1}{n-2})^2$, we find a power saving error term for this count. Since the two results are written in different settings, their similarities might be hidden at first glance. This is why we included Chapter 2, in which we present a unified approach to both results in the setting of constant negative curvature. Writing the arguments in this simple setting helps us emphasize the similarities between the two results.

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)0.006
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 score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.004
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.352
Teacher spread0.323 · 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
Published2023
Admission routes1
Has abstractyes

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