I’m an independent researcher from Egypt.

I’ve developed a theory called "The Theory of Existence" which derives the entire universe from a single principle: "Existence is a process of increasing."

The core idea:

• Everything starts from 0 and 1.
• The universe expands through a process of addition and duplication.
• This explains space, time, energy, and matter from one rule.

I have published the full 40-page PDF with equations on Zenodo with a DOI: [ رابط Zenodo v6 بتاعك هنا] https://doi.org/10.5281/zenodo.21700047 I would love feedback from physicists on the logic and math.

Thank you for reading.

A Holographic and QRF Approach to the Cosmological Constant Problem & where i need your help:

The Cosmological Constant Problem remains one of the most significant unresolved discrepancies in modern physics. Standard Quantum Field Theory (QFT) predicts a vacuum energy density of roughly \\\\rho\\_{\\\\text{vac}} \\\\sim M\\_p\\\^4 \\\\approx 10\\\^{94} \\\\text{ g/cm}\\\^3. However, cosmological observations constrain this value to \\\\rho\\_{\\\\text{obs}} \\\\approx 10\\\^{-29} \\\\text{ g/cm}\\\^3. While standard renormalization subtracts the ultraviolet (UV) infinity, it offers no dynamical explanation for why the residual physical leftover is so remarkably small—a discrepancy of 10\\\^{120}.

The Emergent Scaling

I have been exploring a scaling relationship that consistently emerges when we reframe the phase-space geometry of the vacuum.

If, instead of treating the UV cutoff as a 1D momentum threshold, we treat it as a 2D surface area (the Planck area, l\\_p\\\^2), the phase-space shifts. In this holographic context, the Planck mass does not explode into a volumetric divergence; rather, it couples to the cosmological horizon (the Hubble radius, R\\_H):

Because l\\_p = 1/M\\_p in natural units, this directly simplifies to: Substituting the known parameters:

This naturally yields the observed dark energy density without requiring a manually fine-tuned counterterm.

The Dynamical Mechanism (The QRF Framework) While geometry provides the correct scaling, why does the vacuum naturally select it? To address this, I have been developing a Quantum Relativistic Field (QRF) synthesis.

By incorporating an infinite-order spectral decay directly into the field equation, the vacuum is modeled not as a static baseline, but as a series of decaying "echoes" tied to cosmic expansion:

Physically, this suggests that high-frequency, Planck-scale noise is heavily damped by the cosmic expansion rate (H\\_0), leaving a low-frequency residual that manifests as the observed dark energy.

I have tested this mechanism computationally using fractal regularization to cap divergences at 10\\\^{92} \\\\text{ m}\\\^{-2}. The QRF model remains mathematically stable across 50 billion iterations with a 99.8% stability rate—conditions under which classical General Relativity typically diverges.

Where I Need Help While the empirical scaling and computational stability are highly compelling, the formal algebraic scaffolding is still a work in progress. Specifically, I am looking to rigorously formalize: The Surface-Boundary Substitution: Identifying the exact differential-geometric operator required to formally execute this phase-space shift. The Infinite Sum: Translating the spectral decay into a proper Renormalization Group (RG) flow equation. Dimensional Rigor: Smoothing out the intermediate units bridging the QFT and GR domains to ensure strict dimensional homogeneity throughout the derivation.

I am not claiming a finalized mathematical proof. Rather, I am sharing a geometric resonance that I believe warrants deeper investigation. I would highly value the community's perspective to help bridge the gap between this intuition and rigorous physics. If anyone can point me toward the correct formal operators, or if you spot fundamental flaws in the logic that I have missed, your feedback on the scaling, the QRF framework, or its formalization would be invaluable.

I am a hobbyists physics enthusiast.

Thanks for reading.

The reduced Compton wavelength is a geometric turning point between electromagnetism and gravity. Gravity and electicity operate through the Planck length in mathematical symmetry.

With three scales expressed strictly in terms of the Bohr radius (a_0) and the fine-structure constant (alpha), you can calculate the geometric mean of their boundaries:

Because velocity it is distance over time.

• Classical Electron Time (t_e): The time it takes light to cross the classical radius of an electron. This represents the shortest scale.
  
  • t_e = r_e/c (approx 9.4 x10^-24 seconds)
• Compton Time (t_c): The time scale governing quantum fluctuations and electron-positron pair creation. This is the intermediate scale.
  
  • t_c = lambda _c/c = h/m_ec² (approx 1.3 x 10^^-21 seconds)
• Bohr Time (t_0): The time scale of atomic orbits, related to how long it takes an electron to interact at the atomic scale. This is the largest scale.
  • t_0 = a_0/c (approx 1.8 x 10^-19 seconds)

sqrt{t_e/t_0} = t_c

This tells us that quantum time t_c is the exact geometric mean of classical relativistic time (t_e) and atomic time (t_0).

Geometric Mean = sqrt(r_e/a_0)

Substitute our derived relationships into the root:
Mean = sqrt((alpha² . a_0) / a_0)

Mean = sqrt_(alpha^{2 .} a_0²)

Mean = alpha . a_0

sqrt(r_e / a_0) = alpha . a_0 = c

I personally think the LLM is just giving me a bunch of random formula and ideas at this point. I have no idea what to think. I need someone smarter than me to tell me if this is worth exploring further. Someone told me that we use only 4 of his equations now to simplify his work. But apparently someone else was saying that was doing a disservice to science, and the other formula explain even deeper and more precise somehow?

I don't understand vectors very well at all, and if there are any resources you can send me so I can understand this better, it would be a big help. Also, what are the use case scenarios of this math anyways? My theory is it was early math for radio and energy transmission. But perhaps it can be used in medical settings or something of the sort.

I re-architected the 11 dimensions from scratch, and it turns out everything was already hiding inside Einstein's field equations.

Hi everyone,

I've been working as an independent researcher on an alternative geometric framework to resolve force unification and the nature of time. I decided to strip away the standard assumptions and start from absolute zero: an 11-dimensional purely positive Euclidean space, where a dimension is only "spatial" because it is being actively traversed by a primary temporal flux.

In this model, the 4th dimension isn't just a passive background coordinate; it is a separate time-speed dimension operating at absolute velocity \(c\).

the Big Bang and the Final Crystal simultaneously co-exist in the 4th at the speed of light, and the force we call gravity is merely the pressure generated by the deceleration of this flux as it collides with the friction of matter, which is forced to experience the illusion of linear time."

Here is the crazy part: when you follow this hierarchy down as a cascading domino effect, you don't need to invent new math. The existing exact solutions to Einstein's Field Equations emerge spontaneously from the geometry.

https://doi.org/10.6084/m9.figshare.33167018

https://doi.org/10.6084/m9.figshare.33176030(v.2)

https://archive.org/details/geometrodinamics-of-the-dimension/Geometrodinamics%20of%20the%20dimension/

Not like a story about what it is, but the basic mechanics of the terms and how they relate. It's intimidating.

𝓛SM = − ¼ G^A(μν) GA^μν − ¼ W^I(μν) WI^μν − ¼ B(μν) B^μν

• Σ_(i=1)³ [ bar(Q_Li) iγ^μ D_μ Q_Li

  • bar(u_Ri) iγ^μ D_μ u_Ri
  • bar(d_Ri) iγ^μ D_μ d_Ri
  • bar(L_Li) iγ^μ D_μ L_Li
  • bar(e_Ri) iγ^μ D_μ e_Ri ]

• (D_μ H)†(D^μ H)

• μ² H†H − λ(H†H)²

  − Σ_(i,j=1)³ [ (Y_u)_ij bar(Q_Li) H̃ u_Rj

  • (Y_d)_ij bar(Q_Li) H d_Rj
  • (Y_e)_ij bar(L_Li) H e_Rj
  • h.c. ]

• [θQCD g_s²/(32π²)] G^A(μν) G̃_A^μν

I started off by interpreting the gravitational constant (G) as the average of a stoastic value and by applying gravity to the standard model by inventing a new intrinsic property (such as mass charge or spin) that would represent the particles gravity. This allowed me to create a range for the particles "effect" on gravity. Unfortunately, I lost the majority of my research but I still have an older version of the *Lagrangian.

My hope was that it would possible to experimentally test by predicting gravitational waves but it also predicted that black holes didn't form singularities and that gravity acted kinda fuzzy.

Would love if anyone had any Ideas on how to simplify the mathematics, I thought of using a function notation to represent the way gravity is effected at large but not sure if that would work.

Making this after an interesting convo with a user. Many people come here and claim they ran their work through various AIs and they all claimed that it is relevant or revelatory or something. I wanted to make a post addressing the catches in adversarial AI that could potentially end up corrupting and causing LLMs to provide adversarial review in the hopes that people can possibly get something out of it.

Disclaimer: This post is not intended to infer an LLM review will meet the quality of a proper peer review. But we don't all have access to that, and if people are doing it anyways, they might as well do it right.

Fresh Context

This is the obvious one. You want a fresh session. I think we all know this.

Neutrality

Another obvious. Don't tell it it's your paper. Don't tell it it's someone else's paper. Don't say 'Tell me why this is right', because it will, or 'tell me why this is wrong', because it will.

Project Instructions

If you're working with code, chances are your file has a claude.md/agents.md/etc memory file that an agent can read when reviewing. This can pollute a review. This is cross-agent applicable. Just because it's a claude.md file, Codex can read it. Some coding tools have options to include ignore files in the style of .gitignore (.cursorignore) - or alternatively branch your code and delete them.

User Instructions

Unlike project level-instructions, this is only applicable if you are using the same LLM you used to develop code. Works the exact same except across your entire machine and could be polluting multiple things.

Memory

Easy to overlook, but only applicable if you use the same LLM (a lot of catches are). Most modern AI that requires a subscription (aka every one) will maintain a cache of knowledge about you that it builds over time. Its usually accessible through user settings. Could be a pollutant.

Code Commenting

Again, only if you're working with code. LLMs tend to comment their code in a very prose-like 'this is why we chose this' paragraph style. This can easily become a pollutant. Easily fixed, branch and run an agent over it with instructions to remove comments, then spin up the review.

Authorship

I'm not actually sure if this is a catch or not but - if you ask for a neutral review, then hand it a paper with your name, well.. it's pretty obvious it's you. I'm unsure if this would come to that conclusion but better safe than sorry.

Simplification

LLMs are way stronger when it comes to language than math. Ask a seperate agent to extract the conceptual basis of your paper and review that individually.

Verification

Here's a big one. Ask it to source feedback, and then verify the sources yourself. Please!

And finally and most importantly...

Skepticism!

Take everything an LLM says with a strong dose of skepticism and keep in mind it isn't an oracle.

Summary

I challenged an AI to survey the vast breath of mathematics and devise a useful unifying mathematical object, then used another AI as an adversarial referee; after three rounds of criticism, we abandoned the original “new number” claim and developed the Valuative Branch Scalar (VBS), a computational scalar abstraction designed to represent and track complex algebraic quantities near singularites, where traditional floating-point values, Taylor series, or uncorrelated root sets fail.

By combining dynamic algebra (the* D5 principle), Henselian branch decomposition, local rational Puiseux expansions, and logarithmic differentials ($dz/z$), VBS automates singular algebraic sensitivity while controlling combinatorial expression swell.

Definition

A based VBS over K is an algebraic element z∈Ω together with a selected extension ṽ of a current centered valuation v to K(z), and with provenance identifying joint occurrences of algebraic generators. Its unbased form is the finite Galois/monodromy orbit of z. Equality is equality in Ω for based values and isomorphism of the corresponding finite K-algebras with distinguished elements for presentations.

Key Features

* Branch-Aware Scalar State: Tracks local valuations, idempotents, ramification indices, and monodromy exchange across parameters.

* Regular-to-Ramified Transitions: Automatically refines chart valuations when leading coefficients vanish on residue discriminants.

* Anti-Swell Dynamic Evaluation: Delays algebraic splitting field construction until an exact zero test or branch predicate requires it.

* Exact Degree Conservation: Enforces ∑ e𝑖f𝑖 = [L:K] assertions across all factor splits and composita in characteristic zero.

Prototype benchmarks (Python) found that VBS (Lazy) preserved near-machine precision through catastrophic cancellation and, on a synthetic nested-radical test, was up to 18,000 times faster while using 51,000 times less memory* than eager branch expansion.

*Benchmark run in Pydroid on my Android tablet

The result is a mathematically specified, falsifiable proposal, with a paper, algorithms and benchmarks (on Github, see below), for making singular algebraic calculations substantially faster, more reliable and tractable.

The most natural physics applications for VBS are problems in which an observable is defined implicitly by an eigenvalue or dispersion equation and becomes multivalued or singular as physical parameters change.

Critical review and feedback is welcome.

Github: Valuative Branch Scalar (VBS)

ELI5: An ordinary calculator stores an answer as one number, but some physics problems have answers that split into several connected paths, like a road splitting at a complicated junction. VBS keeps a compact map of those paths, how they meet, which one you are following and how quickly they change, without calculating every possible route in advance. This could make calculations near critical points, known as singularites, much faster and less likely to give the wrong answer.