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Record W2963590284

Blow-Ups in Generalized Complex Geometry

2016· article· en· W2963590284 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2016
Typearticle
Languageen
FieldMathematics
TopicHomotopy and Cohomology in Algebraic Topology
Canadian institutionsUniversity of TorontoUniversity of Waterloo
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsSubmanifoldMathematicsHolomorphic functionSymplectic geometryPure mathematicsPoisson distributionIdeal (ethics)Complex geometryMathematical analysisGeometry
DOInot available

Abstract

fetched live from OpenAlex

Generalized complex geometry is a theory that unifies complex geometry and symplectic geometry into one single framework. It was introduced by Hitchin and Gualtieri around 2002. In this thesis we address the following question: given a generalized complex manifold together with a submanifold, does the blow-up of that submanifold admit again a generalized complex structure? We give the following answers to this question: If the directions that are normal to the submanifold are purely complex, then the blow-up admits a generalized complex structure for which the blow-down map is generalized holomorphic if and only if the induced Lie algebra on the conormal bundle of the submanifold is degenerate. This is a rather restrictive condition, but it is always satisfied if the submanifold is of complex codimension two. On the other extreme, if all the normal directions are symplectic, then we show that the blow-up always admits a generalized complex structure, provided the submanifold is compact. We then also give an example of a submanifold that is not of the above two types, and show that it can not be blown up. Finally, we also address the analogous question in generalized Kähler geometry. Given a generalized Kähler manifold together with a submanifold, we show that under certain geometric constraints on the submanifold the blow-up is again generalized Kähler.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.055
GPT teacher head0.314
Teacher spread0.258 · 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.

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

Citations9
Published2016
Admission routes1
Has abstractyes

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