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Record W7047431123

Hilbert's fourteenth problem and finite generation ideals

2025· other· en· W7047431123 on OpenAlexaff

Bibliographic record

VenueWhite Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · 2025
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsYork University
Fundersnot available
KeywordsCounterexampleInvariant (physics)Homogeneous spaceIdeal (ethics)Finitely-generated abelian groupAlgebraic numberAlgebra over a fieldIntuition
DOInot available

Abstract

fetched live from OpenAlex

Hilbert's fourteenth problem asks whether invariant rings under algebraic group actions are always finitely generated. There are a number of examples that have been constructed since the mid-20th century which demonstrate that this is not the case in general. This thesis is concerned with developing our understanding of these non-finitely generated invariant rings. This goal is ambitious, as by their nature these rings are difficult to work with and it is hard to build an intuition for what might be true in general. The difficulty of trying to develop a solid intuition from examples is exacerbated by the process of ``removing symmetries,'' which relates some of the more well-understood invariant rings. A key construction we employ in order to better understand the structure of these counterexamples to Hilbert's problem is the finite generation ideal, consisting of invariants which make the invariant ring finitely generated after localisation. We take a number of paths in order to achieve our aim, including computing the finite generation ideal for existing examples, constructing new counterexamples, and improving our understanding of both the process of removing symmetries and the finite generation ideal itself. Specifically, we first compute the finite generation ideal of a famous counterexample due to Daigle and Freudenburg. Next, we work on constructing new non-finitely generated invariant rings, focusing primarily on an example proposed by Maubach. We then investigate this process of removing symmetries on some new examples. Finally, we study the finite generation ideal in the setting of monomial algebras, with the intention of passing results obtained to SAGBI-bases; a form of generating set we employ to compute the finite generation ideal for invariant rings.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0020.006
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.015
GPT teacher head0.207
Teacher spread0.192 · 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 routes1
Has abstractyes

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