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Numbers May Build the Universe, Not Just Describe It

A plain-language version of “Number Theory as Physics”

2 min readNo jargon, no mathematicsPhysics

The short version

This paper says our belief in smooth, continuous space and time comes from how our senses evolved, not from nature itself. It proposes that reality is built from discrete tree-like structures governed by scaling ratios like pi and the golden ratio, with the smooth world we experience emerging only at larger scales.

Why we see smoothness that may not exist

Our brains tell us the world is continuous. But this is a survival trick, not the truth.

Our eyes contain millions of separate light sensors. Our skin contains separate touch sensors. The brain blends these discrete signals into what feels like smooth experience. We then invented mathematics that matches this feeling: the "real numbers" that fill in all the gaps between counting numbers.

The paper says this is like a fish thinking water is the only possible medium. We favor smooth mathematics because we evolved to perceive smoothness. Other minds might have invented very different math.

The finger-counting problem

We write numbers in base-10 because humans have ten fingers. The paper calls this the "pentadactyl problem." The ratio of a circle's edge to its width, called pi, gets written as 3.14159... only because we use base-10. In a different base, it would look completely different. The ratio itself is real. Our way of writing it is not.

The paper argues that physical constants written in decimal form are not revealing deep truths. The constants themselves, as pure ratios, matter more than any digit string.

A new kind of number based on scaling

The paper proposes "q-adic" numbers. These use any scaling ratio, not just whole number primes. Pi, the golden ratio, and the growth number e can all serve as scaling bases. This frees physics from human counting habits.

These q-adic systems describe tree-like structures where each level branches by the chosen ratio. The smooth numbers we use in everyday physics emerge only at the boundary of these trees, through a process the paper calls the Monna map.

What this means for space, time, and matter

The paper applies this idea across physics. Space and time become ordering relationships on tree structures, not fundamental substances. Particle masses become patterns in the tree geometry. Forces become ways the tree can change shape. The expanding universe becomes a tree growing new branches.

Quantum randomness arises from information lost when we project the full tree onto our limited measurements. What we call "now" depends on how coarsely we observe the underlying structure.

What the paper does not show

The paper presents a broad framework, not proven facts. It does not derive the exact values of particle masses from first principles. It does not show that q-adic mathematics makes predictions different from standard physics in ways we can currently test. Many proposed tests remain future possibilities.

The framework leaves open whether any particular scaling ratio is truly fundamental, or whether many ratios might compete. It also leaves open whether the tree structure itself requires explanation, or is simply assumed as given.

Words used here

q-adic
a number system using any scaling ratio, not just whole number primes
Monna map
a method to produce smooth-looking numbers from tree structures
pentadactyl
having five fingers, used here to describe our base-10 counting habit

Learn more in plain language

This plain-language version was written by an AI model from the text of the paper and checked against plain-language rules: everyday words, no mathematics, no unexplained names. It leaves details out and can still be wrong; the paper is the source of record. To report a problem, open the paper, select the passage and choose Report.

For specialists: the technical digest, quoted from the paper

In the paper's words

This chapter transitions from theoretical derivation to empirical verification, identifying specific signatures of the q-adic framework within the fields of quantum information and condensed matter physics. We propose a primary, testable prediction: the existence of Prime-Periodic and Ratio-Periodic Noise in quantum devices. We argue that environmental decoherence in qubits is not purely stochastic but is modulated by the hierarchical energy barriers of the underlying ultrametric substrate, resulting in spectral peaks at frequencies f_n = n f₀ log q.

The abstract, verbatim, and its opening sentence is the claim. Every line below is quoted from the text.

Numbers it reports

  1. Relationships as Mathematical Signatures: As noted earlier, the electron-muon mass ratio 206.768 approximates $3^5/(π·e)$ with 0.02% accuracy.

    from Numerical
  2. The proton-electron mass ratio 1836.152 has been noted to approximate $6π^5$ (yielding 1836.12, off by 0.02%).

    from Numerical
  3. Approximations: While individual numerical coincidences can be dismissed, the collective pattern across all particle mass ratios suggests they are topological invariants of the underlying discrete graph: Electron-muon mass ratio : $m_\mu/m_e \approx 206.768$ is remarkably close to $3^5/(\pi \cdot e) \approx 206.768$ (accurate to 0.02%) Proton-electron mass ratio : $m_p/m_e \approx 1836.152$ approximates $6\pi^5 \approx 1836.118$ (0.00188% error, within $1.9\sigma$ of experimental value)

    from Notable Numerical
  4. The electron-muon ratio derives from: $$\frac{m_\mu}{m_e} = e^{5} \cdot C_{\text{boundary}} \cdot A_{\text{aut}}$$ where: - $e^5 \approx 148.413$ represents pure exponential scaling over five hierarchical levels - $C_{\text{boundary}} = \pi/(\pi-1) \approx 1.4669$ arises from the Monna map relating tree boundary to real line - $A_{\text{aut}} \approx 0.949$ comes from automorphism group PGL(2, $\mathbb{Q}_e$) symmetries Combining these factors: $148.413 \times 1.4669 \times 0.949 \approx 206.8$, matching the experimental value within 0.2%.

    from 10.4
  5. Muon-Tau Ratio: Following similar reasoning: $$\frac{m_\tau}{m_\mu} = e^{d_\tau - d_\mu} \cdot \frac{f_\tau}{f_\mu} = e^3 \cdot \frac{\phi^2}{e} \approx 20.086 \times 0.852 \approx 17.11$$ compared to experimental $16.8167(13)$ (error 1.7%).

    from 17.2.2 Lepton Mass
  6. Results: Ratio Best $q$-adic Expression Match Precision $\log_{10} B_i$ $m_\mu/m_e$ $e^5 \cdot \pi/(\pi-1) \cdot A_{\text{aut}}$ 0.05% 2.1 $m_\tau/m_\mu$ $e^3 \cdot \phi^2/e$ 1.7% 1.3 $m_p/m_e$ $6\pi^5$ (effective) 0.002% 3.8 $m_n/m_p$ $1 + \alpha/\pi$ 0.0004% 4.2 $m_W/m_Z$ $\sqrt{1 - (2\pi\alpha)^2}$ 0.02% 2.7 $m_t/m_b$ $2\pi^2$ (approx) 4% 0.8 Combined Evidence: Assuming independence (reasonable for different particle sectors): $$\log_{10} B_{\text{total}} = \sum_i \log_{10} B_i = 2.1 + 1.3 + 3.8 + 4.2 + 2.7 + 0.8 = 14.9$$ Thus: $$B_{\text{total}} = 10^{14.9} \approx 8 \times 10^{14}$$ This constitutes decisive evidence against the null hypothesis.

    from 17.2.4 Bayesian Model

How it is done

  1. The Democratic Mathematical Arena Ostrowski’s theorem and completions of $\mathbb{Q}$ The adelic perspective: $\mathbb{R} \times \prod _{p} \mathbb{Q}_{p}$ Generalized valuations beyond integer primes Physical quantities as adelically invariant

    from Chapter 3:
  2. Measurement and Determinism Quantum measurement as projection to real component Hidden variables as tree depth information Non-locality from common ancestry in tree Bell’s theorem in q-adic context

    from Chapter 9:
  3. The brain performs what mathematicians would recognize as a reconstruction from discrete samples—effectively implementing a biological version of the Nyquist-Shannon sampling theorem.

    from 1.1
  4. The fundamental theorem of arithmetic guarantees unique prime factorization, making primes the irreducible multiplicative building blocks of $\mathbb{Z}$.

    from 1.2

What would falsify it

  1. and Future Tests The framework makes specific, falsifiable predictions: Prediction 17.3 (Resonance Spectrum at Colliders): New particles should appear at masses: $$m_n = m_0 q^n, \quad n = 1,2,3,\dots$$ with $q \approx e$ or $\pi$ and $m_0$ around electroweak scale.

    from 17.4.2 Falsifiability
  2. Prediction 17.4 (Gravitational Wave Echoes): Black hole merger signals should show post-merger echoes with time delays: $$\Delta t_n = t_0 + n \tau \log q$$ where $\tau \propto M_{\text{BH}}$ and $q \approx e$.

    from 17.4.2 Falsifiability
  3. Prediction 17.5 (Fundamental Constant Variations): If dimensionless constants vary, they should do so in discrete steps at times: $$t_n = t_0 q^n$$ rather than continuously.

    from 17.4.2 Falsifiability

Where the claim stops

  1. While not yet definitively proven, the $q$-adic framework has moved from mathematical speculation to empirically testable theory.

    from 17.5 Conclusion:
  2. It challenges our basic assumptions about reality, consciousness, and knowledge.

    from Conclusion: The Final
  3. Visual processing begins with discrete photoreceptor cells in the retina sampling light at approximately 120 million points (rods) and 6 million points (cones).

    from 1.1

Where to read

  1. Chapter2,372 words · 10 min
  2. Chapter2,247 words · 10 min
  3. Chapter2,273 words · 10 min
  4. Chapter1,750 words · 8 min
  5. Chapter 5:1,702 words · 7 min
  6. Chapter2,090 words · 9 min
  7. Chapter1,584 words · 7 min
  8. Chapter2,098 words · 9 min
  9. Chapter2,758 words · 12 min
  10. Chapter2,135 words · 9 min
  11. Chapter3,287 words · 14 min
  12. Chapter 12:2,609 words · 11 min

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