Artian’s Origami

Quantum Traction Theory emblem

Field Notes · Quantum Traction Theory

Artian’s Origami

24, 32, 96, 97 — the numbers in the theory are not numbers anyone chose. They are creases in a single folded sheet, forced by geometry. And here is how I get my brilliant, lazy AI study partner to find every one of them in the book — even when the labels lie.

Ali Attar · Colombes, France · June 2026 · 14 min read


The fastest way to dismiss a physics theory is to catch it choosing numbers. Someone needs a 24 here, a 32 there, and — how convenient — in they go, tuned until the answer fits. That is not a theory; that is decoration. So let me say it plainly, because it is the first half of this post: 24, 32, 96, 97, … are not numbers you choose. Not one of them is a dial. Every single one is derived — and they all come from one place, a single act of folding the book calls Artian’s Origami.

I know this cold, because I have spent a great many late nights proving it to the most stubborn study partner I own: an AI assistant who, bless it, behaves exactly like a brilliant kid dodging homework. Ask it something hard and it would honestly rather tell me the answer isn’t in the book than get up and go look for it. So this post is two things at once — where the numbers come from, and how I get my AI to actually find them, page by page, usually by leaning over its shoulder and saying the thing my own father used to say to me: go back and look harder, son. It’s in there. :-)

And I am going to explain all of it the way I would to a sharp sixteen-year-old — no jargon, no notation you need a degree to decode. That is not me dumbing it down; it is the honest test. If a number is truly forced by geometry, with no knob hidden anywhere, then I should be able to show you exactly where it comes from in plain words. Jargon is very often where fudge-factors hide — a thicket of symbols is a wonderful place to bury a number you actually just chose. So if Artian’s Origami is real, a high-schooler should be able to follow every single fold.

Here is the picture, and it is genuinely simple and beautiful. The ontology lives in Section 1.3, page 85: start with one flat sheet of paper — a strip that loops once around and meets itself, a full circle, 2π. Nothing else exists. Then it folds. To be anything at all — a particle, a force, a mass — is to be a fold in that sheet. And the moment you fold, geometry takes over and decides everything: how many creases, at what angles, in what order. You don’t get to vote. The fold is what we are; the geometry is what fixes the numbers.

I · The first two creases · pp. 192–193

Where 24 and 32 come from

One rule does all the work, stated on pages 192–193: no naked cubes. The smallest piece of space is not allowed to be a little box, because a box has built-in favourite directions — its edges point along three axes, and a universe made of boxes would have a secret “up” baked in before anything happened. So the smallest piece must be rotationally fair: the same from every direction. A sphere, not a cube.

That single demand hands you the first two numbers, with no freedom at all:

Page 193, stated outright

24 — how many of the smallest space-atoms (“pixellates”) complete one balanced bundle. A sphere that fits inside a box fills π/6 of it (pure geometry-class fact), and it takes exactly 24 of those to add up to one fully-spherical bundle (24 × π/6 = 4π). So 24 = whole bundle ÷ one atom — the book writes it VSQ / Vpix = 24. Counted, not chosen.

32 — the same question for surface instead of volume: how many smallest area-tiles cover one complete surface (both sides of a sphere). The geometry gives exactly 32, written QΣ / Smin = 32. So 32 = whole surface ÷ one tile. Also counted, also not chosen.

These are not lucky integers. They are ratios — “how many pieces in the whole” — as fixed as “a triangle has 180 degrees.” You could not change them without changing geometry itself. There is a half-angle cousin to this on pages 1217–1219, where the same folding logic takes a half-turn and halves it three times (180° → 90° → 45° → 22.5°) to land on the angle π/8 — again with no dial, just forced folds.

II · The rest of the family · pp. 142, 959–961, 971, 1046

Every other number is built from those two

Once you have the creases, the bigger numbers are folds of the creases — combinations, never new inventions. The light-meson readout windows are gathered on page 142 and derived in full from page 1046 onward:

  • 80 = 24 + 32 + 24 — the neutral pion’s readout: two volume-bundle creases and one surface crease, stacked (p. 142).
  • 96 = 3 × 32 — the charged pion: three complete surface addresses. A charged thing exposes itself to the lab differently from a neutral one, so it gets three surface tiles, not the neutral mix. 96 is just 32, folded three times (pp. 1046–1048).
  • 37 = 32 + 4 + 1 — appears in the Higgs radial-mode mass: the surface number plus small fixed pieces, no new ingredient (pp. 971, 983).
  • 97 = 3 × 32 + 1 — the muon’s “co-location recovery” crease: the charged-particle 96, plus one. Even this one — the number that looks most like it might be arbitrary — is the surface count folded three times and nudged by a single unit (pp. 959–961).

Notice the pattern: neutral things, charged things, and heavier cousins systematically get different creases — and which creases you get is fixed by what the particle physically is (its charge, its flavour), not by what answer you are hoping for. That is the opposite of fitting. The bricks are forced by geometry; the recipe is forced by the particle’s identity.

And the order matters — deeply. These pieces are not thrown in a bag and added. Each crease sits where it sits for a reason the book spells out on page 1046: which fold is the area exposure, which is the four-to-three thickness projection, which is the co-location recovery. The arrangement carries an ontological meaning — it says what the particle is doing to the sheet — and that reasoning is laid out fold by fold. The numbers are not just correct; they are correct in a particular order, for a particular reason.

III · A note on the labels · pp. 959–961

Why 97 still wears a “fragile” tag - a good example

If you go looking, you will find 97 still marked “fragile” around pages 959–961. There is a story behind such outdated badges, and one author with two custom-trained AI assistants — one commercial, one public, each running around $200 a month. The flag is not saying 97 is a free parameter — it plainly isn’t; it is 3 × 32 + 1. It marks something narrower: the deeper unified derivation of the whole charged-lepton rank family (the set 256, 384, 198, 97 that fixes the electron, muon and tau together) was still being tightened.

There is also a timing wrinkle that is mine to own. I stopped updating the public Zenodo main branch at a certain point — for reasons that are a story for another day — and the book kept working on exactly this question after that freeze. So some public-facing “fragile” labels are simply older than the work that has since firmed them up. The crease was always geometric; the label just hasn’t caught up with the cleanup. Which is the perfect bridge to the second half of this post — because that stale label is exactly the kind of thing that sends my AI study partner home saying “I couldn’t find it, Dad.”


IV · Reading it yourself

No, son. Look again.

All of this is in the book, on pages you can turn with your own hands — page 959 for the muon’s 97, page 1218 for the π/8 fold. But let’s be honest about how a person actually reads a twelve-hundred-page book in 2026: they hand it to an AI and ask. So here is everything I have learned about getting my clever, lazy study partner to do its homework properly — and it really is parenting, not programming.

My AI is the most brilliant librarian you will ever meet, and the laziest. Ask it something hard and its first instinct is to lean on the desk and tell you, with total confidence, that the library does not have that book. It would rather reassure you the answer isn’t there than walk to the back and check the shelf. It is not being stupid — it is a gifted kid who would rather guess than study. And like any gifted kid, it responds beautifully to someone who simply will not accept “I couldn’t find it.”

There are two honest reasons it gives up early. One: it cannot hold the whole book in its head. Twelve hundred pages is far more than it can look at in one go — the amount it can actually keep in view, its “context window,” is a fraction of that — so it cannot read cover to cover; it has to search: jump to a page, read a slice, come back. Two: when its first guess misses, it quits — it searches for the one phrase it expected, doesn’t see it, and announces “this appears to be unfinished,” as if one look settled the matter. That is the kid coming home swearing the library didn’t have the book when really he glanced at one shelf and gave up.

It happened to me on the fine-structure constant — the number that sets the strength of electromagnetism. I asked whether the book derives it or just fits it. My AI looked, came back, and told me, very seriously, that the proof was unfinished; the book itself flagged it “pending.” It was right that a label said so. It just hadn’t noticed the label was a fossil. So I did the only thing that works. I sent it back to study.

How that conversation actually went

Me: Hold on, kiddo — you didn’t look deep enough. That “pending,” where did you even find it? An early chapter?

The AI: …you’re right, it’s from an earlier section. Let me check whether it was finished later.

Me: There you go. Ignore the label, go dig properly — I promise it’s in there.

The AI: …Found it! Pages 317 to 319. A full printed theorem — exactly five rails, proven you can’t have more and can’t have fewer, no hidden knob, built only from the geometry numbers fixed earlier. The early “pending” was never updated. I gave up too soon.

Me: That’s my boy.

That is the whole game in one exchange. The answer had been sitting on pages 317–319 the entire time. The label was expired! And the only thing standing between “this is unfinished” and “here is the ten-digit derivation” was a parent’s oldest line: go back and look harder — it’s in there.

V · The method

The seven things I say to make it study

So here is the whole playbook I use on my brilliant, lazy study partner — and that you can use on yours. None of it is clever; it is just a parent refusing to accept “I couldn’t find it.”

  1. Give it the whole book, not a summary. Hand over the actual book — the open-access record is at doi.org/10.5281/zenodo.17527179 — not a chapter you hope is the right one. If your AI can run code, ask it to convert the PDF to plain text and write a one-line helper that prints any page on request; then “show me page 193” returns page 193, word for word. If it can’t run code, upload the PDF directly so it can search inside it. Get the book on Zenodo ↗
  2. Tell it to search, not to remember. Say it at the start: “Don’t answer from training or memory. Search the file, find the page, read it, then answer — and give me the page number.” This one sentence flips it from confidently guessing to actually opening the book.
  3. When the first search misses, change the words. It searches literally. If “uniqueness proof” finds nothing, the proof may be filed under “strict theorem,” “residual,” “no free parameter,” or a symbol. Hand it three or four phrasings. Most “it’s not in the book” answers are nothing but a vocabulary mismatch — the kid looking up the wrong word in the index.
  4. Say “go to the next page.” Long derivations spill across pages; it reads one, hits the page break, and stops as if the thought ended there. Just say “next page.” The π/8 fold runs 1217 to 1219; the α theorem runs 317 to 319 — the punchline is almost always one page over from the setup.
  5. Double-check every “pending” label — some of them are genuine, but most of them are outdated. This is the one that matters most for this book. Because I shipped it raw, a “pending / to-be-derived / yellow” flag in an early chapter may have been finished hundreds of pages later (see 97, above). So whenever it reports “the book says this is unfinished,” reply: “that label may be outdated — go and check whether it was derived later.” Nine times in ten it comes home holding the finished proof.
  6. Make it quote, not paraphrase. “Show me the actual lines, not your summary.” This catches it inventing something that merely sounds right — and catches you reading what you wished the book said. If it can’t produce the lines, it didn’t find it.
  7. Run a critic and an advocate — in two separate sessions. In one chat, open with: “Be my harshest reviewer. Find the weakest link. Where could this be fitting instead of deriving?” A flattering study partner is useless — tell the kid to try to break the book, and watch what is still standing afterward. Then, in a different session (a fresh one, not the same conversation), flip the role: ask it to be the theory’s advocate — to read the deep layers of the book and bring you the strongest answers it can find, with the page numbers. One kid hunts for the cracks; the other kid defends the house. Read both, side by side, and the truth sits where they meet — that is how you get a balanced answer out of an AI instead of whichever mood it happened to be in.

VI · The deeper move · pp. 139–142

Same equation or number, different physics

There is one idea the Origami makes natural, set out around pages 139–142, and it is how QTT relates to the physics you already know. Often QTT and standard physics write down the same equation, or land on the same number — and the difference is not the arithmetic. It is the physics underneath.

Same equation or number, different physics: the textbook computes it; the fold explains why it had to be that and nothing else.

Classical thermodynamics computed entropy correctly for fifty years before anyone could say what entropy was. Both pictures gave the same number; one was a calculation, the other an explanation. The Origami sits in that second seat. When it reproduces a known mass or a known constant, it is not racing the textbook to the same digits — it is saying here is the fold that makes those digits forced. On page 142 you can watch this happen in front of you: an internal η-meson value that sits a catastrophic 31 standard deviations from experiment becomes a +0.1σ agreement once it is read through its proper finite window — same object, with the readout fold printed in the open rather than hidden as a fit.

VII · One sheet, folded

The whole thing in one breath

So when you see the numbers — 24, 32, 80, 96, 97, and the rest — do not read them as a list of constants someone picked. Read them as creases in one sheet of paper. One flat strip of capacity, looping once at 2π (p. 85); one rule forbidding favourite directions (pp. 192–193); and then a discipline of folding that produces every number in the theory, each in its place, each for a reason (pp. 1046, 959–961). That is Artian’s Origami: same paper first, the declared fold second, the readout third.

It is a genuinely beautiful way for Artian’s universe to be built and I am everyday in awe — not assembled from a parts bin of arbitrary constants, but folded, once, out of a single sheet. And the test of it is exactly as it should be: not whether the math is beautiful, or elegant, but whether the creases follow the Artian’s universe behavior. So far, fold after fold, they do — and every one of them is on a page you can turn.

So when the machine tells you, with total confidence, that the answer isn’t in the book — do what I do. Smile, lean over its shoulder, and say: no, son. Look again. It’s in there. :-)

Related field notes

Three linked pieces of the same clock story

QTT

Read these together: the origami map of the book, the tabletop clock-tilt test, and the speed-of-light clarification that keeps the 7.6% factor in the right physical channel.


Quantum Traction Theory · Ali Attar · quantumtraction.org · The book (Zenodo) · ORCID

Comments

Leave a comment

Check also

View Archive [ -> ]