Read Me / Guide

This page is your map to everything on jremnt.com.

Evans Node Dialect (also called Matrix Node Theory – MNT) was developed by one independent researcher, with the help of modern AI tools, over roughly five focused months spread across a single year. The goal was not just to sketch a “cool idea”, but to build something that:

• has a clear ontology (what exists),
   
• comes with an explicit mathematical framework,
   
• is checked against real data, and
   
• is easy to attack with human review and AI-assisted analysis.
   

This guide tells you:

1. What each document is for,
    
2. How to approach the theory depending on who you are, and
    
3. How to test it, stress it, and try to break it.
    

This guide is written for four types of visitors:

• Curious reader – you’ve heard “Theory of Everything” and want the big picture in plain language.
   
• Student / self-taught learner – you want to see how a unification attempt is structured and how it connects to known physics.
   
• Working scientist / serious reviewer – you care about assumptions, equations, fits and falsifiability.
   
• AI-augmented analyst – you plan to use tools like ChatGPT, Gemini, Claude, Wolfram, or Julius to audit the framework.
   

If you see yourself in more than one group, pick the deepest track that feels comfortable.

Very short version:

Evans Node Dialect (END / MNT) models the universe as a lattice of fundamental “nodes.”
Energy, space, time, and fields are all collective behaviours of these nodes.
The framework aims to:

 recover known quantum and gravitational physics,

reproduce many measured constants from a small set of global parameters, and

make explicit, falsifiable predictions for future data.

 

The documents on this site are not meant to be mysterious. They are designed so that:

• a layperson can understand the story and implications,
   
• a physicist can reconstruct the logic and math, and
   
• an AI tool can reproduce key derivations and compare them with public data.
   

Think of the theory as a five-piece toolkit, plus a main preprint.

File / SectionRole in the toolkitRead this when…PreprintCore Evans Node Dialect / MNT paper: main narrative, definitions, and key equations.You want the “official” theory description.MNT_Axioms_Ontology.pdfLists assumptions and ontology: what nodes are, what is fundamental vs emergent, what is not assumed.You want to understand the conceptual foundations before committing to the math.MNT_Math_Lexicon.pdfDictionary of symbols, quantities, and recurring structures.You are reading the preprint / proofs and need a quick reminder of notation.MNT_Structural_Proofs.pdfStep-by-step derivations showing how lattice assumptions generate familiar structures (fields, interactions, conservation laws).You want to check whether the “node → field → observable” chain is coherent.MNT_Global_Validation.pdfCollects comparisons between the framework’s outputs and external data (particle physics, cosmology, astrophysics) in one place.You want to know “How well does this actually match what we measure?”MNT_END_Companion.pdfCompanion / commentary: motivation, development timeline, interpretation notes, and change log.You prefer a guided tour with context, or you want to see how the framework evolved over ~1 year.CC-Patent / Licensing pageClarifies how the work may be shared, used, and cited.You want to reuse figures, run simulations, or build on the ideas while respecting attribution. 

You don’t have to read everything in order. Use the next section to choose a track.

If you care more about ideas than equations:

1. Read the Introduction page on the site.
    
2. Read the FAQ, focusing on sections:
    
   • “Big-picture questions,”
      
   • “What are nodes?”,
      
   • “Does this replace QM / GR?”,
      
   • “What makes this different from other ‘TOE’ attempts?”
      

1. Skim the Global Validation summary section or figures to see where the framework touches real data.
    
2. Optional: Read the END Companion introduction to get the story of how the theory was built with help from AI.
    

What you’ll get: a sense of the core idea, why it might matter, and how unusual it is to assemble something this broad in such a short time.

If you’ve had some physics and want to dive deeper:

1. Start with the END Companion:
    
   • It explains the motivation, language, and roadmap in plain terms.
      

1. Move to the Preprint:
    
   • Read the abstract, introduction, and conclusion first.
      
   • Then work through the sections that interest you most (e.g., quantum side, gravity side, cosmology).
      

1. Keep Math Lexicon open:
    
   • Whenever a symbol or construction is unfamiliar, look it up there instead of guessing.
      

1. Glance at Structural Proofs:
    
   • Pick one chain you care about (e.g., “how do we get something like the Standard Model?”) and follow only that part.
      

1. Finish with Global Validation:
    
   • See which claims touch real-world measurements and where uncertainties are still large.
      

What you’ll get: a structured example of how a unification attempt is built and checked, and a good playground for learning how to read unconventional theoretical work.

If your instinct is “show me the assumptions, show me the fits, show me the failures”:

1. Start with MNT_Global_Validation.pdf.
    
   • Identify which observables the framework claims to hit (constants, spectra, masses, cosmological parameters, etc.).
      
   • Note where results are presented as derivations vs fits vs qualitative alignments.
      

1. Then open MNT_Axioms_Ontology.pdf.
    
   • Check the basic ontology: What is declared fundamental? What symmetries / structures are assumed?
      
   • Decide whether you accept, reject, or want to modify those assumptions.
      

1. Move to MNT_Structural_Proofs.pdf.
    
   • Follow at least one full derivation chain all the way through.
      
   • Ask: “Is every nontrivial step justified, or are there hidden assumptions?”
      

1. Use MNT_Math_Lexicon.pdf as your dictionary:
    
   • Treat it like the index of a long monograph.
      

1. Read the Preprint front-to-back (or section-by-section in your area of expertise).
    
   • Mark any places where:
      
     • a claim appears stronger than the derivation,
        
     • a numerical example could be swapped for a full error analysis, or
        
     • a parameter choice looks like a hidden tune.
        

1. Optionally skim the END Companion last:
    
   • It can help you see why certain design choices were made, and where the author expects objections.
      

What you’ll get: enough context to write a serious referee report, internal note, or “here’s where this stands” memo, without needing to reverse-engineer the entire project.

If you want to use an AI tool as a “junior postdoc”:

1. Download the PDFs you want to use (typically all 5 + the preprint).
    
2. In your AI interface (Code Interpreter, Wolfram, Julius, etc.), upload:
    
   • MNT_Axioms_Ontology
      
   • MNT_Math_Lexicon
      
   • MNT_Structural_Proofs
      
   • MNT_Global_Validation
      
   • MNT_END_Companion
      
   • and the main Preprint.
      

1. Use a meta-prompt such as:
    

Audit Prompt (short version)

“You are a critical theoretical-physics assistant.
I’ve uploaded several PDFs describing the Evans Node Dialect / Matrix Node Theory.
 First, read the axioms and ontology and summarise the core assumptions.

Then identify which physical constants and observables the framework claims to derive or match.

Reproduce, as far as possible, those derivations numerically from the given parameter set.

Compare the results with current PDG / Planck / LIGO / cosmology values, listing percentage deviations.

Highlight any places where the derivation is incomplete, an extra parameter is introduced, or tuning seems likely.

Suggest concrete experimental or observational tests that would most strongly confirm or falsify the framework in the next 5–10 years.”

 

1. Ask your AI to:
    
   • generate code/notebooks for key derivations,
      
   • re-run fits using public data,
      
   • propose stress-tests and alternative explanations.
      

What you’ll get: an independent, tool-based view of where the framework is strong, where it’s fragile, and where it needs more work.

If you want to verify as much as possible with finite effort, here is a recommended ladder:

1. Check internal consistency
    
   • Do the ontology, axioms, and structural proofs fit together without obvious contradictions?
      
   • Are conservation laws, symmetries, and limiting cases (e.g., classical limits) handled sensibly?
      

1. Reproduce a small set of key numbers
    
   • Pick a handful of core quantities (for example: fine-structure-constant–type results, a representative mass, a cosmological parameter).
      
   • Follow the derivations in Structural Proofs and Math Lexicon to see how these are obtained.
      
   • Use your own code or an AI tool to compute the results independently.
      

1. Cross-check with public data
    
   • Compare the framework’s values with PDG, Planck, LIGO/Virgo, or other standard compilations.
      
   • Note not only where the numbers are “close”, but where assumptions or error bars are under-stated.
      

1. Look for over-fitting
    
   • Ask: “How many truly free global parameters are being used?”
      
   • For each derived quantity, ask whether that parameter was fixed before or after you see the data.
      

1. Probe known tensions
    
   • Focus on areas where existing physics has puzzles (muon g-2, W mass, Hubble tension, neutron-star radii, dark-matter searches, etc.).
      
   • Compare what END/MNT says in those regions with both the standard model expectations and current measurements.
      

1. Attempt falsification
    
   • Identify experiments, surveys, or analyses that would most sharply distinguish END/MNT from the status quo.
      
   • If possible, encode these as “if–then” statements:
      
     • If observable X is measured outside range Y, this version of the framework is ruled out.
        

The point is not to treat the theory as fragile or sacred, but as a testable, evolving object.

If you are sceptical (you should be), here are good places to aim:

• Assumptions:
  Does any core axiom conflict with well-established theorems or with your understanding of quantum field theory / GR / cosmology?
   
• Scaling / limits:
  Do the node-lattice constructions give the right behaviour in known limits (low energy, high energy, near-classical, deep quantum)?
   
• Parameter economy:
  Are the claimed “few global parameters” really sufficient, or are hidden knobs being dialed in different sectors?
   
• Missing phenomena:
  Are there clear observational facts that the framework does not mention or cannot reproduce?
   
• Predictive sharpness:
  Are the predictions for future experiments specific enough that they can be cleanly falsified?
   

Feedback pointing out failures is extremely valuable. If your analysis finds clear contradictions or mis-matches, you are invited to share those critiques so they can be documented and addressed in future revisions.

If you write about, critique, or build on Evans Node Dialect / MNT, you can:

• Link to jremnt.com as the primary source.
   
• Refer to the main preprint as:
   Jordan Ryan Evans, “Evans Node Dialect (Matrix Node Theory): [full title of preprint]”, 2025, jremnt.com.
  
   
• When reproducing figures, tables, or code snippets:
   
  • include attribution to Jordan Ryan Evans and the specific PDF/file name.
     

For details on licensing and permitted reuse, please see the CC-Patent / Licensing page.

• For high-level concept & story → read the Introduction and END Companion.
   
• For technical derivations → open Math Lexicon + Structural Proofs alongside the Preprint.
   
• For data and numbers → dive into Global Validation (and the upcoming “Predictions & Tests” section if present).
   
• For hands-on verification with AI → follow the Track D instructions above.
   

If you found something impressive, confusing, wrong, or worth improving, that’s the point:
this framework is shared so that it can be examined, tested, and pushed—by people and by machines.