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Record W4402337923

A Rigorous Analysis of M31's Dynamics Using Surreal Mathematics and Category Theory

2024· preprint· en· W4402337923 on OpenAlexaff
Joseph Spurway

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2024
Typepreprint
Languageen
FieldComputer Science
TopicMatrix Theory and Algorithms
Canadian institutionsMount Royal University
Fundersnot available
KeywordsDynamics (music)MathematicsStatistical physicsMathematical economicsComputer scienceSociologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a comprehensive mathematical framework that integrates surreal numbers, category theory, and quantum information theory to analyze the complex dynamics of the Andromeda galaxy (M31). By leveraging the Process of Quantum Information (PQI) framework, we apply these advanced mathematical constructs to empirical data, particularly the rotational velocities, mass distribution, and luminosity profiles derived from the seminal work of Vera Rubin and her collaborators. Surreal numbers, with their capacity to represent both infinitesimal and infinite values, offer a robust tool for capturing the full range of observed quantities and their inherent uncertainties. Category theory provides the structural foundation to generalize the relationships between these mathematical objects, ensuring consistency and coherence in the analysis. Furthermore, the integration of quantum information theory introduces a nuanced layer of interpretation, accounting for quantum effects that may influence large-scale astronomical observations. This interdisciplinary approach not only enhances our theoretical understanding of M31 but also contributes to the broader discourse in astrophysics by offering novel insights into the interplay between dark matter and baryonic matter in galaxies. The methodologies developed in this study have the potential to be applied to other cosmic systems, paving the way for future research in the intersection of quantum mechanics and cosmology.

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)0.008
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0000.001
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 head0.013
GPT teacher head0.239
Teacher spread0.227 · 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
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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