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Record W7132927122

Broken Toric Varieties and Hypertoric Hitchin Systems

2025· dissertation· W7132927122 on OpenAlexafffund
Evan Sundbo

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldMathematics
TopicAdvanced Combinatorial Mathematics
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsSubvarietyCohomologySheafToric varietySheaf cohomologySpectral sequenceBetti numberAlgebra over a fieldConstant (computer programming)
DOInot available

Abstract

fetched live from OpenAlex

In the first part of this thesis we study the cohomology of broken toric varieties via the derived push-forward of the constant sheaf to a complex of polytopes, using it to prove a Deligne-type decomposition theorem and degeneration of the associated Leray-Serre spectral sequence. We discuss certain maps between broken toric varieties and how they descend to maps of cohomology groups. Furthermore, we give a description of the Betti numbers of some broken toric varieties whose associated complex of polytopes is the n-skeleton of a higher dimensional polytope, encompassing some important examples. In the second part we investigate hypertoric Hitchin systems, whose cohomology is governed by a subvariety which is broken toric. After reviewing their construction, we give a new proof of a deletion-contraction relationship on these varieties (first proven by Dansco-McBreen-Shende) and refine it to a statement about the cohomology of certain sheaves on the polytopal complex. Using these facts and the general results in the first part of the thesis, we develop tools for calculating the cohomology of some families of hypertoric Hitchin systems inductively, given knowledge of some base cases. In particular, this yields explicit formulae for the Poincaré polynomials of hypertoric Hitchin systems associated to graphs with first Betti number 2.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.034
GPT teacher head0.355
Teacher spread0.321 · 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
Published2025
Admission routes2
Has abstractyes

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