thank you for the contribution :)

https://github.com/Cosmolalia/akataleptos-geodesic-constants...

We present observational and computational evidence that the large-scale filamentary structure of the universe is topologically equivalent to a Menger sponge at finite iteration depth. Recent work has demonstrated that thirteen fundamental physical constants can be derived from the seven structural parameters of the Menger sponge (S=5, P=2, b=3, d=3, Δ=17, removed=7, kept=20) with zero free parameters and sub-parts-per-billion precision for dimensionless quantities. If these constants genuinely originate from Menger geometry, the physical universe should exhibit Menger-like topology at observable scales. We compile observational data from WMAP, Planck, NEXUS+, IllustrisTNG, EAGLE, and other surveys and simulations to test this prediction across eight independent metrics. We find: (1) the cosmic energy budget (WMAP: 73% dark energy, 27% matter) matches the Menger first-iteration void/structure ratio (74.07/25.93) to within 1%; (2) the cosmic web volume void fraction (NEXUS+: 76%) corresponds to Menger iteration 4.7, consistent with 13.8 billion years of finite-time evolution; (3) cosmic filaments are one-dimensional at their core, carry over 50% of total mass in under 6% of total volume, and exhibit hierarchical self-similarity down to at least 10 parsec scales, matching the Menger construction algorithm at every tested scale; (4) the mathematical tools used to identify cosmic web structures (Morse theory, persistent homology, discrete topology) are the same formalism used to characterize Menger-type fractals. We propose that discrepancies between observed and ideal Menger ratios arise from the universe being at finite iteration depth with spatially varying iteration rates due to gravitational time dilation, yielding testable predictions including a spatial dipole in the fine structure constant correlated with local matter density.

I ran hierarchical analysis: only 23% of peak ratios match algebraic combinations of constants. Not "peaks everywhere" — a specific structure.

But the weirder part: I simulated dimensional reduction (3D→1D collapse, like nuclear pasta phases in neutron stars) and watched what happens to constants:

- Geometric constants (φ, π, e): 99%+ accuracy throughout - Wave constants (α≈137, mp/me≈1836): 13% in 3D → 99.9% in 1D

The wave constants EMERGE during dimensional collapse. Not fitted — emerged from a physical process.

I'm calling it "Capellini Geodesic Extrusion Felting" — the phase where constants crystallize from topology under dimensional pressure.

Code, data, visualizations: https://github.com/Cosmolalia/akataleptos-geodesic-constants... Full writeup: [https://open.substack.com/pub/quantummarmelade/p/capellini-g...]

Three independent paths now converge on the same constants. Either profound or profoundly wrong.

Collaboration/critique welcome: SylvanGaskin@gmail.com

I always thought there was a connection between geometry and the math and physical constants. Once I was thinking about Einstein's equivalence principle between gravity and acceleration and his elevator-in-space argument. He claimed that there is no experiment that the man in the elevator could do to determine if he was in a gravity field or accelerating rocket. It occurred to me that all he had to do was wait because the rocket could not accelerate at 9.81 m/s forever. So I did the math lightspeed/acceleration of gravity = 30559883.59 sec = 353.7023 days for 86,400 sec/day or 96.9% of a year to get to c. Just a coincidence, they say.

Look at a chart of sin(x) + sin(x/2) + sin(x/3) + sin(x/5) + sin(x/7) + sin(x/11) + sin(x/13) + sin(x/17) + sin(x/19) + sin(x/23) + sin(x/29) + sin(x/31) + sin(x/37) + sin(x/43), you can find a local peak close to practically any number; the chart is effectively entirely composed of peaks.

It's extremely unsurprising that you would find peaks near mathematically relevant numbers, since there are peaks near any number whatsoever. You could pick ten random numbers out of a hat and fine tune those to 99.999%+ accuracy as well using the same scaling procedure.

# Target constants CONSTANTS = { 'fine_structure': 131.11, 'phi': 1.9, 'pi': 3.6, 'e': 2.4, 'sqrt_2': 1.1, 'sqrt_3': 1.2, 'sqrt_5': 2.5,

Best results: L = 3017.391610 s = 0.042000 Average: 94.848564% Minimum: 82.509479%

  Constants:
    sqrt_2                   : 100.00000000%
    sqrt_3                   : 99.99236291%
    phi                      : 99.93928922%
    pi                       : 99.89806320%
    e                        : 99.88623436%
    sqrt_5                   : 99.85340314%

- You are a real person who genuinely wants to make a difference in the field of physics

- The proposed mathematics isn't technobabble and actually does generate the constants you say it does

- The contributions are overwhelmingly yours, not overwhelmingly AI-generated

Even under these generous assumptions, this just isn't how citizen science is done. Your first step isn't publishing a 2-page paper with no references and basically no details on what you're doing or why. Your first step is taking your results to the nearest PHd theoretical physicist you can find, and getting them to take you seriously so you can find out if your work actually has merit.

- "Man who says it can not be done, should not interrupt man who is doing it."