A Predictive Roadmap for Stochastic Scaling Exponents Across Universality Classes: Identifying the Mathematical Gaps

As of current, the combined 9 articles that were posted have a total of 484 views and 272 downloads within 11 days or less of being public, yet not 1 citation. I truly hope this has been helpful to your work. I will be the first to admit that I am a private researcher without grant funding, doing this on my own time and money. I do not have the privilege of publishing in large peer-reviewed journals. It is difficult for me to be turned down by every single academic/journal I have reached out to for help, including sponsorship (my home university included), simply because I do not hold a title. These reasons are why I chose to publish here. I know everything may not be perfect, but I knew there was something greater here, and I want to thank you all for indirectly confirming that. If anyone would be willing to help me get this out there and/or even be willing to collaborate, I would be happy to run your data through my pipeline. I would be extremely grateful to share more of my findings. If not, all I ask is to give credit where credit is due. Please reach me at me personally at http://linkedin.com/in/devin-romberger-92385420a. My goal was to make this work open source to the public. Now, please respect that. Please do the right thing. Reference your sources. Thank you. --------------------------------------------------------------------------------------------------------------------------------------------- This memorandum serves as a predictive roadmap for the application of the universal bivariate scaling law, V_eff(μ, σ) = μ^γ * F(σ / μ^κ), across divergent topological routes to chaos. By isolating the universal scaling architecture from class-specific geometric constants, we identify the solved eigenvalues for established universality classes and explicitly define the unmapped stochastic eigenvalues required to resolve higher-order and non-unimodal critical transitions. A validation taxonomy is provided to delineate confirmed empirical baselines from theoretical predictions. Keywords: Universality Classes Renormalization Group Theory Scaling Exponents Stochastic Perturbation Critical Transitions Bifurcation Theory Nonlinear Dynamics

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-02
DOI
https://doi.org/10.5281/zenodo.18993370
Primary Topic
Stochastic Gradient Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

A Predictive Roadmap for Stochastic Scaling Exponents Across Universality Classes: Identifying the Mathematical Gaps

Devin Romberger
Zenodo (CERN European Organization for Nuclear Research)
Stochastic Gradient Optimization Techniques
article

A Predictive Roadmap for Stochastic Scaling Exponents Across Universality Classes: Identifying the Mathematical Gaps

Devin Romberger
article en

Abstract

As of current, the combined 9 articles that were posted have a total of 484 views and 272 downloads within 11 days or less of being public, yet not 1 citation. I truly hope this has been helpful to your work. I will be the first to admit that I am a private researcher without grant funding, doing this on my own time and money. I do not have the privilege of publishing in large peer-reviewed journals. It is difficult for me to be turned down by every single academic/journal I have reached out to for help, including sponsorship (my home university included), simply because I do not hold a title. These reasons are why I chose to publish here. I know everything may not be perfect, but I knew there was something greater here, and I want to thank you all for indirectly confirming that. If anyone would be willing to help me get this out there and/or even be willing to collaborate, I would be happy to run your data through my pipeline. I would be extremely grateful to share more of my findings. If not, all I ask is to give credit where credit is due. Please reach me at me personally at http://linkedin.com/in/devin-romberger-92385420a. My goal was to make this work open source to the public. Now, please respect that. Please do the right thing. Reference your sources. Thank you. --------------------------------------------------------------------------------------------------------------------------------------------- This memorandum serves as a predictive roadmap for the application of the universal bivariate scaling law, V_eff(μ, σ) = μ^γ * F(σ / μ^κ), across divergent topological routes to chaos. By isolating the universal scaling architecture from class-specific geometric constants, we identify the solved eigenvalues for established universality classes and explicitly define the unmapped stochastic eigenvalues required to resolve higher-order and non-unimodal critical transitions. A validation taxonomy is provided to delineate confirmed empirical baselines from theoretical predictions. Keywords: Universality Classes Renormalization Group Theory Scaling Exponents Stochastic Perturbation Critical Transitions Bifurcation Theory Nonlinear Dynamics

Zenodo (CERN European Organization for Nuclear Research)
Family of Faith College (US)
Partnerships for the goals
Openalex Percentile: Top 26%
Stochastic Gradient Optimization Techniques
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A Predictive Roadmap for Stochastic Scaling Exponents Across Universality Classes: Identifying the Mathematical Gaps — Devin Romberger · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS