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Record W6986279639

p-adic geometry and dynamics

2016· dissertation· en· W6986279639 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2016
Typedissertation
Languageen
FieldMathematics
Topicadvanced mathematical theories
Canadian institutionsnot available
Fundersnot available
KeywordsJulia setMandelbrot setField (mathematics)Dynamics (music)Construct (python library)Quadratic equationSection (typography)Complex dynamics
DOInot available

Abstract

fetched live from OpenAlex

Complex dynamics in a single variable is a well-studied field pioneered by Gaston Julia and Pierre Fatou.It deals with the iteration of rational maps on the Riemann sphere.Many beautiful fractal images arise such as the Mandelbrot set or the Julia sets of functions.As explored in [Sil07], dynamical systems has applications to arithmetic problems.The idea prompting this thesis was to look at the dynamics of p-adic correspondences and derive arithmetic information.We start our study of dynamics with the classical complex case.A quick diversion into nonarchimedean analysis is then needed before we move on to nonarchimedean dynamics, initially over P 1 (K) where K is a nonarchimedean field.Many results similar to those in the complex setting hold in this nonarchimedean situation.After illustrating some of these similarities, as well as some differences, we move on to build the theory of nonarchimedean geometry.Starting from the basics, we construct the category of rigid analytic spaces and give some important examples.These spaces, while interesting in their own right, are not true topological spaces and hence not apt spaces on which to study dynamics.In light of this, we construct Berkovich spaces (this time truly topological spaces) in the next section and give many examples.In our penultimate section, we look at how to define dynamics on P 1 Berk (K) by taking advantage of the tree structure.Finally, we explore some questions about dynamics of nonarchimedean correspondences, focusing specifically on the quadratic case.for their help with this thesis and more generally my development as a mathematician and researcher.They both have spent many hours over the past few years explaining things to me as well as working together on problems.In a field that can make it hard to maintain self-confidence, my supervisors were always kind, supportive, and intelligent.Their wealth of knowledge about technical details and support for my research career were incredibly useful.The idea for this thesis formed in the summer of 2014 when I was doing summer research with Professors Goren and Kassaei as an undergraduate student.Two other undergraduate students, Eric Stubley and Nicolas Resch, were working with me at the time.They were both wonderful to work with, very passionate, and taught me a ton of math.I wouldn't be the same caliber mathematician if it wasn't for their help.I would like to thank all my fellow mathematics students at McGill for working on problems with me, hanging out when I didn't want to work, and generally creating a nice community.Helen, the mathematics graduate program coordinator, provided invaluable help with my degree.I also received financial support during my Master's program from NSERC, my co-supervisors, and the McGill mathematics department in the form of a

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.165
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.021
GPT teacher head0.287
Teacher spread0.266 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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