The Universal Binary Principle (UBP)

This repository is a work in progress and may contain errors that I have missed fixing or flagging. I am actively working to tidy it up.

The code here is available for study and may be valuable to others. I encourage you to explore the system. It's my hope that someone with superior knowledge and experience will explore this repository, find something they can use, and develop it further than I have.

Many of these studies are merely a beginning and can be extended significantly. I often stopped a study once I found the specific UBP system function I needed, leaving the groundwork for others to continue.

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Key Takeaways from My UBP Research

This section outlines the core concepts I've explored while working on the UBP system:

1. Virtual Computation and Core Restraint: You can achieve virtual computation by correctly establishing a core constraint.

   • I use geometry with a "TGIC" (Three-axis, Six faces, Nine Interactions) model.
   • When computation is restricted by this geometry, calculations become a spatial inquiry.

2. Multiple Dimensions: In a virtual environment, multiple dimensions are possible.

   • I utilize a 24-bit "OffBit" structure stacked into four layers.
   • Each layer represents a dimension of information, but the concept can become significantly more complex.

3. Geometry as Error Correction: Geometry (structure) acts as an inherent error correction mechanism within a virtual environment.

4. Operators as Tools: Numerical and logical operators (such as mathematics, physics equations, graphs, and matrices) become tools to manipulate information (data) in the virtual environment.

   • There's no need to invent new concepts; existing ones are useful and required parts of the system.
   • This also enables reverse-engineering solutions: we obtain evidence first, then try to determine the underlying "why" and "how."

5. Reversible Systems: A correctly aligned system should be able to operate in reverse.

   • Just as a mathematical equation must be balanced around the mighty equals sign ($=$), a computational system should do the same.
   • This ability means we can look at the Information and determine the observable outcome.

6. Information-First Perspective: I am currently exploring what the Information-First perspective means and how to employ it systematically.

   • The concept is that information precedes Time, Space, and all observables.
   • Does it have fundamental rules? Can we use those rules for a specific purpose?
   • Can an Information-First perspective (a lens on a problem) uncover anything interesting?

Repository Purpose

This repository is an ongoing effort to document and explore the UBP project through written papers and executable notebooks. It serves as both a knowledge base and an interactive environment for analysis, experiments, and sharing insights about UBP.

Repository Contents and Study Philosophy

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Documentation Structure

All formal documentation is provided here as PDFs, numbered sequentially from 01 (oldest) to the most recent.

I have also included dedicated folders for each major study conducted from a specific point in development onward. While I have strived for completeness, please note that some elements may have been accidentally omitted.

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Code and Study Philosophy

My work is fundamentally driven by empirical verification. The code in this repository consists primarily of Python scripts designed to verify if a concept is tangible and real or purely theoretical.

Key Principles:

• Exclusion Policy: Any concept that failed verification or lacked developmental value has been excluded. Therefore, everything you find here is material I deemed valuable for either system development or the results were worth pursuing.
• Focus on Utility: I consistently aim my studies toward practical and verifiable outcomes. The UBP system development required real-world data, so my research was intentionally focused on problems that would satisfy UBP's developmental requirements while yielding helpful and measurable results.

🚀 Getting Started with the UBP Repository

We recommend starting with the most stable and well-documented system in this repository to minimize initial friction.

1. Primary Starting Point

I suggest beginning with ubp_3.6:

• Repository Link: ubp_3.6
• Reasoning: Version 3.6 is a well-worked-out operating system and is designed to be more stable than earlier prototypes. Starting here will provide the best environment for early experimentation.

2. Execution Environment Options

The code consists of Python scripts and can be run in any modern Python environment.

Environment	Benefit	Note
Cloud Notebooks	Rapid setup and AI Assistance	Platforms like Google CoLab or Kaggle Notebooks are excellent for creating and running scripts. CoLab, in particular, offers useful AI assistance for implementation.
Local System	Full control	Running Python scripts directly in your local terminal provides the highest control. I have also had success using Anaconda Navigator for managing environments.

Once a solid notebook or local script environment is established, you can easily add cells or modules to explore specific uses of the UBP system.

3. Advanced Experimentation with AI Agents

For complex studies and rapid iteration on the UBP framework, I have successfully utilized specific AI environments that treat the system as a callable tool:

💡 AI Agent Workspaces

These tools allow you to instruct an AI (like Gemini) to use your UBP scripts as functions, acting as an intelligent partner for research:

• AI Agent Workspace V4.0 (Recommended):

  • Description: An AI agent powered by Function Calling and a real client-side Python (Pyodide) sandbox.
  • How I Use It: I fill this workspace with UBP Python scripts. The agent can then search the web, execute code, manage files, and generate plots with high accuracy.
  • Link: AI Agent Workspace V4.0

• Manus AI (Hands-on Guidance Required):

  • How I Use It: I connect Manus AI to the ubp_3.6 or gpu_ubp repository and instruct it to use the system to conduct a study.

• AI Realm Architect (Sophisticated IDE):

  • Description: A sophisticated, browser-based Python Development Environment (IDE) powered by Gemini. It uses Pyodide to run a full Python interpreter in the browser via WebAssembly.
  • Key Features for UBP: The AI assistant uses "tools" to create, read, and manage files in a Virtual File System (including a /persistent_state folder). This allows you to build and run complex, stateful data workflows entirely in the browser.
  • Link: AI Realm Architect

Contributing

• Caveat: All of these ai assisted methods require careful, hands-on directing to prevent the AI from defaulting to its own interpretations, simplifications, or placeholders.

Contributions are welcomed. If you have improvements or suggestions, feel free to open an issue or pull request. I would really like to see what others do with the UBP system - please let me know!

License

This repository is provided for educational and research purposes.

Author

• DigitalEuan

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This repo is a work-in-progress attempt at writing papers and documenting UBP. Expect ongoing updates and new notebooks as the project develops.