Stability First: A Personal Programme for Re-reading Particle Physics

Over the past years, I have written a number of papers on physics—mostly exploratory, sometimes speculative, always driven by the same underlying discomfort.

Not with the results of modern physics. Those are extraordinary.
But with the ordering of its explanations.

We are very good at calculating what happens.
We are less clear about why some things persist and others do not.

That question—why stability appears where it does—has quietly guided much of my thinking. It is also the thread that ties together a new manuscript I have just published on ResearchGate:

“Manuscript v0.2 – A stability-first reinterpretation of particle physics”
👉 https://www.researchgate.net/publication/398839393_Manuscript_v02

This post is not a summary of the manuscript. It is an explanation of why I wrote it, and what kind of work it is meant to enable.

Not a new theory — a different starting point

Let me be clear from the outset.

This manuscript does not propose a new theory.
It does not challenge the empirical success of the Standard Model.
It does not attempt to replace quantum field theory or nuclear phenomenology.

What it does is much more modest—and, I hope, more durable.

It asks whether we have been starting our explanations at the wrong end.

Instead of beginning with abstract constituents and symmetries, the manuscript begins with something far more pedestrian, yet physically decisive:

Persistence in time.

Some entities last.
Some decay.
Some exist only fleetingly as resonances.
Some are stable only in the presence of others.

Those differences are not cosmetic. They shape the physical world we actually inhabit.

From electrons to nuclei: stability as a guide

The manuscript proceeds slowly and deliberately, revisiting familiar ground:

the electron, as an intrinsically stable mode;
the proton, as a geometrically stable but structurally richer object;
the neutron, as a metastable configuration whose stability exists only in relation;
the deuteron, as the simplest genuinely collective equilibrium;
and nuclear matter, where stability becomes distributed across many coupled degrees of freedom.

At no point is new empirical content introduced.
What changes is the interpretive emphasis.

Stability is treated not as an afterthought, but as a physical clue.

Interaction without mysticism

The same approach is applied to interaction.

Scattering and annihilation are reinterpreted not as abstract probabilistic events, but as temporary departures from equilibrium and mode conversion between matter-like and light-like regimes.

Nothing in the standard calculations is altered.
What is altered is the physical picture.

Wavefunctions remain indispensable—but they are treated as representations of physical configurations, not as substitutes for them.

Probability emerges naturally from limited access to phase, geometry, and configuration, rather than from assumed ontological randomness.

Why classification matters

The manuscript ultimately turns to the Particle Data Group catalogue.

The PDG tables are one of the great achievements of modern physics. But they are optimized for calculation, not for intuition about persistence.

The manuscript proposes a complementary, stability-first index of the same data:

intrinsically stable modes,
metastable particle modes,
prompt decayers,
resonances,
and context-dependent stability (such as neutrons in nuclei).

Nothing is removed.
Nothing is denied.

The proposal is simply to read the catalogue as a map of stability regimes, rather than as a flat ontology of “fundamental particles”.

A programme statement, not a conclusion

This manuscript is intentionally incomplete.

It does not contain the “real work” of re-classifying the entire PDG catalogue. That work lies ahead and will take time, iteration, and—no doubt—many corrections.

What the manuscript provides is something else:

a programme statement.

A clear declaration of what kind of questions I think are still worth asking in particle physics, and why stability—rather than constituent bookkeeping—may be the right place to ask them from.

Why I am sharing this now

I am publishing this manuscript not as a final product, but as a marker.

A marker of a line of thought I intend to pursue seriously.
A marker of a way of reading familiar physics that I believe remains underexplored.
And an invitation to discussion—especially critical discussion—on whether this stability-first perspective is useful, coherent, or ultimately untenable.

Physics progresses by calculation.
It matures by interpretation.

This manuscript belongs to the second category.

If that resonates with you, you may find the full text of interest.

Jean-Louis Van Belle
readingfeynman.org

Moderation, Measurements, and the Temptation of Ontology

Why physics must resist becoming metaphysics

Some time ago, I found myself involved in what can best be described as an intellectual fallout with a group of well‑intentioned amateur researchers. This post is meant to close that loop — calmly, without bitterness, and with a bit of perspective gained since.

One of the more sensible people in that group bothered to push an interesting article onto my desk, and so I want to talk about that one here.

Gary Taubes, CERN, and an unexpected reinforcement

It’s an article by Gary Taubes on the discovery of the W and Z bosons at CERN, later incorporated into his book Nobel Dreams. Far from undermining my position, the article did the opposite: it reinforced the point I had been trying to make all along.

Taubes does not engage in ontology. He does not ask what W and Z bosons are in a metaphysical sense. Instead, he describes what was measured, how it was inferred, and how fragile the boundary is between evidence and interpretation in large‑scale experimental physics.

This connects directly to an earlier piece I published here:

Something Rotten in the State of QED: A Careful Look at Critique, Sociology, and the Limits of Modern Physics
https://readingfeynman.org/2025/12/01/something-rotten-in-the-state-of-qed-a-careful-look-at-critique-sociology-and-the-limits-of-modern-physics/

Let me restate the central point, because it is still widely misunderstood:

Criticizing the ontologization of W/Z bosons (or quarks and gluons) is not the same as denying the reality of the measurements that led to their introduction.

The measurements are real. The detector signals are real. The conservation laws used to infer missing energy and momentum are real. What is not forced upon us is the metaphysical leap that turns transient, unstable interaction states into quasi‑permanent “things.”

Stable vs. unstable states — a distinction we keep blurring

My own work has consistently tried to highlight a distinction that I find increasingly absent — or at least under‑emphasized — in mainstream physics discourse:

Stable states: long‑lived, persistent, and directly accessible through repeated measurement
Unstable or intermediate states: short‑lived, inferred through decay products, reconstructed statistically

W and Z bosons belong firmly to the second category. So do quarks and gluons in their confined form. Treating them as ontologically equivalent to stable particles may be pragmatically useful, but it comes at a conceptual cost.

It is precisely this cost that I criticize when I criticize mainstream physics.

Not because mainstream physics is “wrong.”
But because it has become too comfortable collapsing epistemology into ontology, especially in its public and pedagogical narratives.

Why this matters now

There is another reason this distinction matters, and it is a forward‑looking one.

The probability that something radically new — in the sense of a fundamentally novel interaction or particle family — will be discovered in the coming decades is, by most sober assessments, rather low. What we will have, however, is:

More precise measurements
Larger datasets
Longer baselines
Better statistical control

In that landscape, progress will depend less on naming new entities and more on bridging what has already been measured, sometimes decades ago, but never fully conceptually digested.

That is where I intend to focus my efforts in the coming years.

Not by founding a new church.
Not by declaring metaphysical revolutions.
But by carefully working at the interface between:

what was actually measured,
what was legitimately inferred,
and what we may have too quickly reified.

Closing note

If there is one lesson I take — from the past dispute, from Taubes, from the history of CERN or fundamental physics in general — it is this:

Physics progresses best when it remains modest about what it claims to be about.

Measurements first. Interpretation second. Ontology, if at all, only with restraint.

That stance may be unsatisfying to those looking for grand narratives. But it is, I believe, the only way to keep physics from quietly turning into metaphysics while still wearing a lab coat.

— Jean Louis Van Belle

Making Sense of What We Already Know…

Living Between Jobs and Life: AI, CERN, and Making Sense of What We Already Know

For decades (all of my life, basically :-)), I’ve lived with a quiet tension. On the one hand, there is the job: institutions, projects, deliverables, milestones, and what have you… On the other hand, there is life: curiosity, dissatisfaction, and the persistent feeling that something fundamental is still missing in how we understand the physical world. Let me refer to the latter as “the slow, careful machinery of modern science.” 🙂

These two are not the same — obviously — and pretending they are has done physics no favors (think of geniuses like Solvay, Edison or Tesla here: they were considered to be ‘only engineers’, right? :-/).

Jobs optimize. Life explores.

Large scientific institutions are built to do one thing extremely well: reduce uncertainty in controlled, incremental ways. That is not a criticism; it is a necessity when experiments cost billions, span decades, and depend on political and public trust. But the price of that optimization is that ontological questions — questions about what really exists — are often postponed, softened, or quietly avoided.

And now we find ourselves in a new historical moment.

The Collider Pause Is Not a Crisis — It’s a Signal

Recent reports that China is slowing down plans for a next-generation circular collider are not shocking. If anything, they reflect a broader reality:

For the next 40–50 years, we are likely to work primarily with the experimental data we already have.

That includes data from CERN that has only relatively recently been made fully accessible to the wider scientific community.

This is not stagnation. It is a change of phase.

For decades, theoretical physics could lean on an implicit promise: the next machine will decide. Higher energies, larger datasets, finer resolution — always just one more accelerator away. That promise is now on pause.

Which means something important:

We can no longer postpone understanding by outsourcing it to future experiments.

Why CERN Cannot Do What Individuals Can

CERN is a collective of extraordinarily bright individuals. But this is a crucial distinction:

A collective of intelligent people is not an intelligent agent.

CERN is not designed to believe an ontology. It is designed to:

build and operate machines of unprecedented complexity,
produce robust, defensible measurements,
maintain continuity over decades,
justify public funding across political cycles.

Ontology — explicit commitments about what exists and what does not — is structurally dangerous to that mission. Not because it is wrong, but because it destabilizes consensus.

Within a collective:

someone’s PhD depends on a framework,
someone’s detector was designed for a specific ontology,
someone’s grant proposal assumes a given language,
someone’s career cannot absorb “maybe the foundations are wrong.”

So even when many individuals privately feel conceptual discomfort, the group-level behavior converges to:
“Let’s wait for more data.”

That is not cowardice. It is inevitability.

We Are Drowning in Data, Starving for Meaning

The irony is that we are not short on data at all.

We have:

precision measurements refined to extraordinary accuracy,
anomalies that never quite go away,
models that work operationally but resist interpretation,
concepts (mass, spin, charge, probability) that are mathematically precise yet ontologically vague.

Quantum mechanics works. That is not in dispute.
What remains unresolved is what it means.

This is not a failure of experiment.
It is a failure of sense-making.

And sense-making has never been an institutional strength.

Where AI Actually Fits (and Where It Doesn’t)

I want to be explicit: I still have a long way to go in how I use AI — intellectually, methodologically, and ethically.

AI is not an oracle.
It does not “solve” physics.
It does not replace belief, responsibility, or judgment.

But it changes something fundamental.

AI allows us to:

re-analyze vast datasets without institutional friction,
explore radical ontological assumptions without social penalty,
apply sustained logical pressure without ego,
revisit old experimental results with fresh conceptual frames.

In that sense, AI is not the author of new physics — it is a furnace.

It does not tell us what to believe.
It forces us to confront the consequences of what we choose to believe.

Making Sense of What We Already Know

The most exciting prospect is not that AI will invent new theories out of thin air.

It is that AI may help us finally make sense of experimental data that has been sitting in plain sight for decades.

Now that CERN data is increasingly public, the bottleneck is no longer measurement. It is interpretation.

AI can help:

expose hidden assumptions in standard models,
test radical but coherent ontologies against known data,
separate what is measured from how we talk about it,
revisit old results without institutional inertia.

This does not guarantee progress — but it makes honest failure possible. And honest failure is far more valuable than elegant confusion.

Between Institutions and Insight

This is not an AI-versus-human story.

It is a human-with-tools story.

Institutions will continue to do what they do best: build machines, refine measurements, and preserve continuity. That work is indispensable.

But understanding — especially ontological understanding — has always emerged elsewhere:

in long pauses,
in unfashionable questions,
in uncomfortable reinterpretations of existing facts.

We are entering such a pause now.

A Quiet Optimism

I do not claim to have answers.
I do not claim AI will magically deliver them.
I do not even claim my current ideas will survive serious scrutiny.

What I do believe is this:

We finally have the tools — and the historical conditions — to think more honestly about what we already know.

That is not a revolution.
It is something slower, harder, and ultimately more human.

And if AI helps us do that — not by replacing us, but by challenging us — then it may turn out to be one of the most quietly transformative tools science has ever had.

Not because it solved physics.

But because it helped us start understanding it again.

Something Rotten in the State of QED? A Careful Look at Critique, Sociology, and the Limits of Modern Physics

Every few years, a paper comes along that stirs discomfort — not because it is wrong, but because it touches a nerve.
Oliver Consa’s “Something is rotten in the state of QED” is one of those papers.

It is not a technical QED calculation.
It is a polemic: a long critique of renormalization, historical shortcuts, convenient coincidences, and suspiciously good matches between theory and experiment. Consa argues that QED’s foundations were improvised, normalized, mythologized, and finally institutionalized into a polished narrative that glosses over its original cracks.

This is an attractive story.
Too attractive, perhaps.
So instead of reacting emotionally — pro or contra — I decided to dissect the argument with a bit of help.

At my request, an AI language model (“Iggy”) assisted in the analysis. Not to praise me. Not to flatter Consa. Not to perform tricks.
Simply to act as a scalpel: cold, precise, and unafraid to separate structure from rhetoric.

This post is the result.

1. What Consa gets right (and why it matters)

Let’s begin with the genuinely valuable parts of his argument.

a) Renormalization unease is legitimate

Dirac, Feynman, Dyson, and others really did express deep dissatisfaction with renormalization. “Hocus-pocus” was not a joke; it was a confession.

Early QED involved:

cutoff procedures pulled out of thin air,
infinities subtracted by fiat,
and the philosophical hope that “the math will work itself out later.”

It did work out later — to some extent — but the conceptual discomfort remains justified. I share that discomfort. There is something inelegant about infinities everywhere.

b) Scientific sociology is real

The post-war era centralized experimental and institutional power in a way physics had never seen. Prestige, funding, and access influenced what got published and what was ignored. Not a conspiracy — just sociology.

Consa is right to point out that real science is messier than textbook linearity.

c) The g–2 tension is real

The ongoing discrepancy between experiment and the Standard Model is not fringe. It is one of the defining questions in particle physics today.

On these points, Consa is a useful corrective:
he reminds us to stay honest about historical compromises and conceptual gaps.

2. Where Consa overreaches

But critique is one thing; accusation is another.

Consa repeatedly moves from:

“QED evolved through trial and error”
to
“QED is essentially fraud.”

This jump is unjustified.

a) Messiness ≠ manipulation

Early QED calculations were ugly. They were corrected decades later. Experiments did shift. Error bars did move.

That is simply how science evolves.

The fact that a 1947 calculation doesn’t match a 1980 value is not evidence of deceit — it is evidence of refinement. Consa collapses that distinction.

b) Ignoring the full evidence landscape

He focuses almost exclusively on:

the Lamb shift,
the electron g–2,
the muon g–2.

Important numbers, yes — but QED’s experimental foundation is vastly broader:

scattering cross-sections,
vacuum polarization,
atomic spectra,
collider data,
running of α, etc.

You cannot judge an entire theory on two or three benchmarks.

c) Underestimating theoretical structure

QED is not “fudge + diagrams.”
It is constrained by:

Lorentz invariance,
gauge symmetry,
locality,
renormalizability.

Even if we dislike the mathematical machinery, the structure is not arbitrary.

So: Consa reveals real cracks, but then paints the entire edifice as rotten.
That is unjustified.

3. A personal aside: the Zitter Institute and the danger of counter-churches

For a time, I was nominally associated with the Zitter Institute — a loosely organized group exploring alternatives to mainstream quantum theory, including zitterbewegung-based particle models.

I now would like to distance myself.

Not because alternative models are unworthy — quite the opposite. But because I instinctively resist:

strong internal identity,
suspicion of outsiders,
rhetorical overreach,
selective reading of evidence,
and occasional dogmatism about their own preferred models.

If we criticize mainstream physics for ad hoc factors, we must be brutal about our own.

Alternative science is not automatically cleaner science.

4. Two emails from 2020: why good scientists can’t always engage

This brings me to two telling exchanges from 2020 with outstanding experimentalists: Prof. Randolf Pohl (muonic hydrogen) and Prof. Ashot Gasparian (PRad).

Both deserve enormous respect, and I won’t reveal the email exchanges because of respect, GDPR rules or whatever).
Both email exchanges revealed the true bottleneck in modern physics to me — it is not intelligence, not malice, but sociology and bandwidth.

a) Randolf Pohl: polite skepticism, institutional gravity

Pohl was kind but firm:

He saw the geometric relations I proposed as numerology.
He questioned applicability to other particles.
He emphasized the conservatism of CODATA logic.

Perfectly valid.
Perfectly respectable.
But also… perfectly bound by institutional norms.

His answer was thoughtful — and constrained.
(Source: ChatGPT analysis of emails with Prof Dr Pohl)

b) Ashot Gasparian: warm support, but no bandwidth

Gasparian responded warmly:

“Certainly your approach and the numbers are interesting.”
But: “We are very busy with the next experiment.”

Also perfectly valid.
And revealing:
even curious, open-minded scientists cannot afford to explore conceptual alternatives.

Their world runs on deadlines, graduate students, collaborations, grants.

(Source: ChatGPT analysis of emails with Prof Dr Pohl)

The lesson

Neither professor dismissed the ideas because they were nonsensical.
They simply had no institutional space to pursue them.

That is the quiet truth:
the bottleneck is not competence, but structure.

5. Why I now use AI as an epistemic partner

This brings me to the role of AI.

Some colleagues (including members of the Zitter Institute) look down on using AI in foundational research. They see it as cheating, or unserious, or threatening to their identity as “outsiders.”

But here is the irony:

AI is exactly the tool that can think speculatively without career risk.

An AI:

has no grant committee,
no publication pressure,
no academic identity to defend,
no fear of being wrong,
no need to “fit in.”

That makes it ideal for exploratory ontology-building.

Occasionally, as in the recent paper I co-wrote with Iggy — “The Wonderful Theory of Light and Matter” — it becomes the ideal partner:

human intuition + machine coherence,
real-space modeling without metaphysical inflation,
EM + relativity as a unified playground,
photons, electrons, protons, neutrons as geometric EM systems.

This is not a replacement for science.
It is a tool for clearing conceptual ground,
where overworked, over-constrained academic teams cannot go.

6. So… is something rotten in QED?

Yes — but not what you think.

What’s rotten is the mismatch

between:

the myth of QED as a perfectly clean, purely elegant theory,
and
the reality of improvised renormalization, historical accidents, social inertia, and conceptual discomfort.

What’s rotten is not the theory itself,
but the story we tell about it.

What’s not rotten:

the intelligence of the researchers,
the honesty of experimentalists,
the hard-won precision of modern measurements.

QED is extraordinary.
But it is not infallible, nor philosophically complete, nor conceptually finished.

And that is fine.

The problem is not messiness.
The problem is pretending that messiness is perfection.

7. What I propose instead

My own program — pursued slowly over many years — is simple:

Bring physics back to Maxwell + relativity as the foundation.
Build real-space geometrical models of all fundamental particles.
Reject unnecessary “forces” invented to patch conceptual holes.
Hold both mainstream and alternative models to the same standard:
no ad hoc constants, no magic, no metaphysics.

And — unusually —
use AI as a cognitive tool, not as an oracle.

Let the machine check coherence.
Let the human set ontology.

If something emerges from the dialogue — good.
If not — also good.

But at least we will be thinking honestly again.

Conclusion

Something is rotten in the state of QED, yes —
but the rot is not fraud or conspiracy.

It is the quiet decay of intellectual honesty behind polished narratives.

The cure is not shouting louder, or forming counter-churches, or romanticizing outsider science.

The cure is precision,
clarity,
geometry,
and the courage to say:

Let’s look again — without myth, without prestige, without fear.

If AI can help with that, all the better.

— Jean Louis Van Belle
(with conceptual assistance from “Iggy,” used intentionally as a scalpel rather than a sycophant)

Post-scriptum: Why the Electron–Proton Model Matters (and Why Dirac Would Nod)

A brief personal note — and a clarification that goes beyond Consa, beyond QED, and beyond academic sociology.

One of the few conceptual compasses I trust in foundational physics is a remark by Paul Dirac. Reflecting on Schrödinger’s “zitterbewegung” hypothesis, he wrote:

“One must believe in this consequence of the theory,
since other consequences which are inseparably bound up with it,
such as the law of scattering of light by an electron,
are confirmed by experiment.”

Dirac’s point is not mysticism.
It is methodological discipline:

If a theoretical structure has unavoidable consequences, and
some of those consequences match experiment precisely,
then even the unobservable parts of the structure deserve consideration.

This matters because the real-space electron and proton models I’ve been working on over the years — now sharpened through AI–human dialogue — meet that exact criterion.

They are not metaphors, nor numerology, nor free speculation.
They force specific, testable, non-trivial predictions:

a confined EM oscillation for the electron, with radius fixed by $\hbar / m_e c$ ;
a “photon-like” orbital speed for its point-charge center;
a distributed (not pointlike) charge cloud for the proton, enforced by mass ratio, stability, form factors, and magnetic moment;
natural emergence of the measured $G_E/G_M$ discrepancy;
and a geometric explanation of deuteron binding that requires no new force.

None of these are optional.
They fall out of the internal logic of the model.
And several — electron scattering, Compton behavior, proton radius, form-factor trends — are empirically confirmed.

Dirac’s rule applies:

When inseparable consequences match experiment,
the underlying mechanism deserves to be taken seriously —
whether or not it fits the dominant vocabulary.

This post is not the place to develop those models in detail; that will come in future pieces and papers.
But it felt important to state why I keep returning to them — and why they align with a style of reasoning that values:

geometry,
energy densities,
charge motion,
conservation laws,
and the 2019 SI foundations of $h$ , $e$ , and $c$
over metaphysical categories and ad-hoc forces.

Call it minimalism.
Call it stubbornness.
Call it a refusal to multiply entities beyond necessity.

For me — and for anyone sympathetic to Dirac’s way of thinking — it is simply physics.

— JL (with “Iggy” (AI) in the wings)

A New Attempt at a Simple Theory of Light and Matter

Dear Reader,

Every now and then a question returns with enough insistence that it demands a fresh attempt at an answer. For me, that question has always been: can we make sense of fundamental physics without multiplying entities beyond necessity? Can we explain light, matter, and their interactions without inventing forces that have no clear definition, or particles whose properties feel more like placeholders than physical reality?

Today, I posted a new paper on ResearchGate that attempts to do exactly that:

“The Wonderful Theory of Light and Matter”
https://www.researchgate.net/publication/398123696_The_Wonderful_Theory_of_Light_and_Matter

It is the result of an unusual collaboration: myself and an artificial intelligence (“Iggy”), working through the conceptual structure of photons, electrons, and protons with the only tool that has ever mattered to me in physics — Occam’s Razor.

No metaphysics.
No dimensionless abstractions.
No “magical” forces.

Just:

electromagnetic oscillations,
quantized action,
real geometries in real space,
and the recognition that many so-called mysteries dissolve once we stop introducing layers that nature never asked for.

The photon is treated as a linear electromagnetic oscillation obeying the Planck–Einstein relation.
The electron as a circular oscillation, with a real radius and real angular momentum.
The proton (and later, the neutron and deuteron) as systems we must understand through charge distributions, not fictional quarks that never leave their equations.

None of this “solves physics,” of course.
But it does something useful: it clears conceptual ground.

And unexpectedly, the collaboration itself became a kind of experiment:
what happens when human intuition and machine coherence try to reason with absolute precision, without hiding behind jargon or narrative?

The result is the paper linked above.
Make of it what you will.

As always: no claims of authority.
Just exploration, clarity where possible, and honesty where clarity fails.

If the questions interest you, or if the model bothers you enough to critique it, then the paper has succeeded in its only purpose: provoking real thought.

Warm regards,
Jean Louis Van Belle

Matter, Energy, Reality ↔ Thought, Intelligence, Consciousness

Dear Reader,

Physics asks: what is matter, energy, reality?
AI asks: what is thought, intelligence, consciousness?

Both are real, both are here. Physics confronts us with particles that behave like waves, with a universe that expands into… what exactly? AI confronts us with machines that converse, that create, that seem to reason — and force us to ask what we mean when we talk about “reasoning,” “creating,” or “understanding.”

This blog began as an attempt to make sense of Feynman’s physics. Over the years, it became a place where I tried to throw back the questions reality throws at us. Physics is real. AI is real. Both invite us to rethink our place in the cosmos, not as masters but as curious observers.

I don’t promise to publish much here — life is busy, and writing takes time — but when I do, it will be in the same spirit: reflecting, questioning, sometimes explaining, never pretending to give final answers.

If you’d like to follow more regular updates, you can always check my LinkedIn profile where I share articles and shorter notes.

Thank you for caring enough to read.

🌀 Two Annexes and a Turtle: Revisiting My Early Lectures on Quantum Physics

Over the past few weeks — and more intensely these past mornings — I’ve returned to two of my earliest texts in the Lectures on Physics series: the first on quantum behavior, and the second on probability amplitudes and quantum interference. Both have now been updated with new annexes, co-authored in dialogue with ChatGPT-4o.

This wasn’t just a consistency check. It was something more interesting: an exercise in thinking with — not through — a reasoning machine.

The first annex (Revisiting the Mystery of the Muon and Tau) tackles the open question I left hanging in Lecture I: how to interpret unstable “generations” of matter-particles like the muon and tau. In the original paper, I proposed a realist model where mass is not an intrinsic property but the result of oscillating charge or field energy — a stance that draws support from the 2019 revision of SI units, which grounded the kilogram in Planck’s constant and the speed of light. That change wasn’t just a technicality; it was a silent shift in ontology. I suspected that much at the time, but now — working through the implications with a well-tuned AI — I can state it more clearly: mass is geometry, inertia is field structure, and the difference between stable and unstable particles might be a matter of topological harmony.

The second annex (Interference, Identity, and the Imaginary Unit) reopens the deeper riddle at the heart of quantum mechanics: why probability amplitudes interfere at all. This annex is the child of years of irritation — visible in earlier, sharper essays I published on academia.edu — with the lazy mysticism that often surrounds “common phase factors.” The breakthrough, for me, was to fully accept the imaginary unit iii not as a mathematical trick but as a rotation operator. When wavefunctions are treated as oriented field objects, not just complex scalars, interference becomes a question of geometric compatibility. Superpositions and spin behavior can then be reinterpreted as topological effects in real space. This is where I think mainstream physics got lost: it started calculating without explaining.

ChatGPT didn’t invent these ideas. But it helped me phrase them, frame them, and press further on the points I had once hesitated to formalize. That’s what I mean when I say this wasn’t just a cleanup job. It was a real act of collaboration — a rare instance of AI not just paraphrasing or predicting, but amplifying and clarifying an unfinished line of human reasoning.

Both revised papers are now live on ResearchGate:

They mark, I think, a modest turning point. From theory and calculation toward something closer to explanation.

And yes — for those following the philosophical side of this project: we did also try to capture all of that in a four-panel comic involving Diogenes, a turtle, and Zeno’s paradox. But that, like all things cartooned by AI, is still a work in progress. 🙂

Post Scriptum (24 June 2025): When You Let the Machine Take the Pen

In the spirit of openness: there’s been one more development since publishing the two annexes above.

Feeling I had taken my analytical skills as far as I could — especially in tackling the geometry of nuclear structure — I decided to do something different. Instead of drafting yet another paper, I asked ChatGPT to take over. Not as a ghostwriter, but as a model builder. The prompt was simple: “Do better than me.”

The result is here:
👉 ChatGPT Trying to Do Better Than a Human Researcher

It’s dense, unapologetically geometric, and proposes a full zbw-based model for the neutron and deuteron — complete with energy constraints, field equations, and a call for numerical exploration. If the earlier annexes were dialogue, this one is delegation.

I don’t know if this is the end of the physics path for me. But if it is, I’m at peace with it. Not because the mystery is gone — but because I finally believe the mystery is tractable. And that’s enough for now.

🧭 From Strangeness to Symbolism: Why Meaning Still Matters in Science

My interest in quantum theory didn’t come from textbooks. It came from a thirst for understanding — not just of electrons or fields, but of ourselves, our systems, and why we believe what we believe. That same motivation led me to write a recent article on LinkedIn questioning how the Nobel Prize system sometimes rewards storylines over substance. It’s not a rejection of science — it’s a plea to do it better.

This post extends that plea. It argues that motion — not metaphor — is what grounds our models. That structure is more than math. And that if we’re serious about understanding this universe, we should stop dressing up ignorance as elegance. Physics is beautiful enough without the mystery.

Indeed, in a world increasingly shaped by abstraction — in physics, AI, and even ethics — it’s worth asking a simple but profound question: when did we stop trying to understand reality, and start rewarding the stories we are being told about it?

🧪 The Case of Physics: From Motion to Metaphor

Modern physics is rich in predictive power but poor in conceptual clarity. Nobel Prizes have gone to ideas like “strangeness” and “charm,” terms that describe particles not by what they are, but by how they fail to fit existing models.

Instead of modeling physical reality, we classify its deviations. We multiply quantum numbers like priests multiplying categories of angels — and in doing so, we obscure what is physically happening.

But it doesn’t have to be this way.

In our recent work on realQM — a realist approach to quantum mechanics — we return to motion. Particles aren’t metaphysical entities. They’re closed structures of oscillating charge and field. Stability isn’t imposed; it emerges. And instability? It’s just geometry breaking down — not magic, not mystery.

No need for ‘charm’. Just coherence.

🧠 Intelligence as Emergence — Not Essence

This view of motion and closure doesn’t just apply to electrons. It applies to neurons, too.

We’ve argued elsewhere that intelligence is not an essence, not a divine spark or unique trait of Homo sapiens. It is a response — an emergent property of complex systems navigating unstable environments.

Evolution didn’t reward cleverness for its own sake. It rewarded adaptability. Intelligence emerged because it helped life survive disequilibrium.

Seen this way, AI is not “becoming like us.” It’s doing what all intelligent systems do: forming patterns, learning from interaction, and trying to persist in a changing world. Whether silicon-based or carbon-based, it’s the same story: structure meets feedback, and meaning begins to form.

🌍 Ethics, Society, and the Geometry of Meaning

Just as physics replaced fields with symbolic formalism, and biology replaced function with genetic determinism, society often replaces meaning with signaling.

We reward declarations over deliberation. Slogans over structures. And, yes, sometimes we even award Nobel Prizes to stories rather than truths.

But what if meaning, like mass or motion, is not an external prescription — but an emergent resonance between system and context?

Ethics is not a code. It’s a geometry of consequences.
Intelligence is not a trait. It’s a structure that closes upon itself through feedback.
Reality is not a theory. It’s a pattern in motion, stabilized by conservation, disrupted by noise.

If we understand this, we stop looking for final answers — and start designing better questions.

✍️ Toward a Science of Meaning

What unifies all this is not ideology, but clarity. Not mysticism, but motion. Not inflation of terms, but conservation of sense.

In physics: we reclaim conservation as geometry.
In intelligence: we see mind as emergent structure.
In ethics: we trace meaning as interaction, not decree.

This is the work ahead: not just smarter machines or deeper theories — but a new simplicity. One that returns to motion, closure, and coherence as the roots of all we seek to know.

Meaning, after all, is not what we say.
It’s what remains when structure holds — and when it fails.

How I Co-Wrote a Quantum Physics Booklet with an AI — And Learned Something

In June 2025, I published a short booklet titled
A Realist Take on Quantum Theory — or the Shortest Introduction Ever.
📘 ResearchGate link

It’s just under 15 pages, but it distills over a decade of work — and a growing collaboration with ChatGPT — into a clean, consistent narrative: electrons as circulating charges, wavefunctions as cyclical descriptors, and action as the true guide to quantum logic.

We didn’t invent new equations. We reinterpreted existing ones — Schrödinger, Dirac, Klein–Gordon — through a realist lens grounded in energy cycles, geometry, and structured motion. What made this possible?

Memory: The AI reminded me of arguments I had made years earlier, even when I’d forgotten them.
Logic: It flagged weak spots, inconsistencies, and unclear transitions.
Humility: It stayed patient, never arrogant — helping me say what I already knew, but more clearly.
Respect: It never erased my voice. It helped me find it again.

The booklet is part of a broader project I call realQM. It’s an attempt to rescue quantum theory from the metaphorical language that’s haunted it since Bohr and Heisenberg — and bring it back to geometry, field theory, and physical intuition. If you’ve ever felt quantum physics was made deliberately obscure, this might be your antidote.

🧠 Sometimes, passing the Turing test isn’t about being fooled. It’s about being helped.

P.S. Since publishing that booklet, the collaboration took another step forward. We turned our attention to high-energy reactions and decay processes — asking how a realist, geometry-based interpretation of quantum mechanics (realQM) might reframe our understanding of unstable particles. Rather than invent new quantum numbers (like strangeness or charm), we explored how structural breakdowns — non-integrable motion, phase drift, and vector misalignment — could explain decay within the classical conservation laws of energy and momentum. That project became The Geometry of Stability and Instability, a kind of realQM manifesto. Have a look at it if you want to dive deeper. 🙂

🔬 When the Field is a Memory: Notes from a Human–Machine Collaboration

Why is the field around an electron so smooth?

Physicists have long accepted that the electrostatic potential of an electron is spherically symmetric and continuous — the classic Coulomb field. But what if the electron isn’t a smeared-out distribution of charge, but a pointlike particle — one that zips around in tight loops at the speed of light, as some realist models propose?

That question became the heart of a new paper I’ve just published:
“The Smoothed Field: How Action Hides the Pointlike Charge”
🔗 Read it on ResearchGate

The paradox is simple: a moving point charge should create sharp, angular variations in its field — especially in the near zone. But we see none. Why?

The paper proposes a bold but elegant answer: those field fluctuations exist only in theory — not in reality — because they fail to cross a deeper threshold: the Planck quantum of action. In this view, the electromagnetic field is not a primitive substance, but a memory of motion — smooth not because the charge is, but because reality itself suppresses anything that doesn’t amount to at least ℏ of action.

🤖 A Word on Collaboration

This paper wouldn’t have come together without a very 21st-century kind of co-author: ChatGPT-4, OpenAI’s conversational AI. I’ve used it extensively over the past year — not just to polish wording, but to test logic, rewrite equations, and even push philosophical boundaries.

In this case, the collaboration evolved into something more: the AI helped me reconstruct the paper’s internal logic, modernize its presentation, and clarify its foundational claims — especially regarding how action, not energy alone, sets the boundary for what is real.

The authorship note in the paper describes this in more detail. It’s not ghostwriting. It’s not outsourcing. It’s something else: a hybrid mode of thinking, where a human researcher and a reasoning engine converge toward clarity.

🧭 Why It Matters

This paper doesn’t claim to overthrow QED, or replace the Standard Model. But it does offer something rare: a realist, geometric interpretation of how smooth fields emerge from discrete sources — without relying on metaphysical constructs like field quantization or virtual particles.

If you’re tired of the “shut up and calculate” advice, and truly curious about how action, motion, and meaning intersect in the foundations of physics — this one’s for you.

And if you’re wondering what it’s like to co-author something with a machine — this is one trace of that, too.

Prometheus gave fire. Maybe this is a spark.

🧭 The Final Arc: Three Papers, One Question

Over the past years, I’ve been working — quietly but persistently — on a set of papers that circle one simple, impossible question:
What is the Universe really made of?

Not in the language of metaphors. Not in speculative fields.
But in terms of geometry, charge, and the strange clarity of equations that actually work.

Here are the three pieces of that arc:

🌀 1. Radial Genesis
Radial Genesis: A Finite Universe with Emergent Spacetime Geometry
This is the cosmological capstone. It presents the idea that space is not a stage, but an outcome — generated radially by mass–energy events, limited by time and light. It’s an intuitive, equation-free narrative grounded in general relativity and Occam’s Razor.

⚛️ 2. Lectures on Physics: On General Relativity (2)
Lectures on GRT (2)
This one is for the mathematically inclined. It builds from the ground up: tensors, geodesics, curvature. If Radial Genesis is the metaphor, this is the machinery. Co-written with AI, but line by line, and verified by hand.

🌑 3. The Vanishing Charge
The Vanishing Charge: What Happens in Matter–Antimatter Annihilation?
This paper is where the mystery remains. It presents two possible views of annihilation:
(1) as a collapse of field geometry into free radiation,
(2) or as the erasure of charge — with geometry as the by-product.
We didn’t choose between them. We just asked the question honestly.

Why This Arc Matters

These three papers don’t offer a Theory of Everything. But they do something that matters more right now:
They strip away the fog — the inflation of terms, the myth of complexity for complexity’s sake — and try to draw what is already known in clearer, more beautiful lines.

This is not a simulation of thinking.
This is thinking — with AI as a partner, not a prophet.

So if you’re tired of being told that the Universe is beyond your grasp…
Start here.
You might find that it isn’t.

—JL

Beautiful Blind Nonsense

I didn’t plan to write this short article or blog post. But as often happens these days, a comment thread on LinkedIn nudged me into it — or rather, into a response that became this article (which I also put on LinkedIn).

Someone posted a bold, poetic claim about “mass being memory,” “resonant light shells,” and “standing waves of curved time.” They offered a graphic spiraling toward meaning, followed by the words: “This isn’t metaphysics. It’s measurable.”

I asked politely:
“Interesting. Article, please? How do you get these numbers?”

The response: a full PDF of a “Unified Field Theory” relying on golden-ratio spirals, new universal constants, and reinterpretations of Planck’s constant. I read it. I sighed. And I asked ChatGPT a simple question:

“Why is there so much elegant nonsense being published lately — and does AI help generate it?”

The answer that followed was articulate, clear, and surprisingly quotable. So I polished it slightly, added some structure, and decided: this deserves to be an article in its own right. So here it is.

Beautiful, but Blind: How AI Amplifies Both Insight and Illusion

In recent years, a new kind of scientific-sounding poetry has flooded our screens — elegant diagrams, golden spirals, unified field manifestos. Many are written not by physicists, but with the help of AI.

And therein lies the paradox: AI doesn’t know when it’s producing nonsense.

🤖 Pattern without Understanding

Large language models like ChatGPT or Grok are trained on enormous text corpora. They are experts at mimicking patterns — but they lack an internal model of truth.
So if you ask them to expand on “curved time as the field of God,” they will.

Not because it’s true. But because it’s linguistically plausible.

🎼 The Seductive Surface of Language

AI is disarmingly good at rhetorical coherence:

Sentences flow logically.
Equations are beautifully formatted.
Metaphors bridge physics, poetry, and philosophy.

This surface fluency can be dangerously persuasive — especially when applied to concepts that are vague, untestable, or metaphysically confused.

🧪 The Missing Ingredient: Constraint

Real science is not just elegance — it’s constraint:

Equations must be testable.
Constants must be derivable or measurable.
Theories must make falsifiable predictions.

AI doesn’t impose those constraints on its own. It needs a guide.

🧭 The Human Role: Resonance and Resistance

Used carelessly, AI can generate hyper-coherent gibberish. But used wisely — by someone trained in reasoning, skepticism, and clarity — it becomes a powerful tool:

To sharpen ideas.
To test coherence.
To contrast metaphor with mechanism.

In the end, AI reflects our inputs.
It doesn’t distinguish between light and noise — unless we do.

Taking Stock: Zitterbewegung, Electron Models, and the Role of AI in Thinking Clearly

Over the past few years, I’ve spent a fair amount of time exploring realist interpretations of quantum mechanics, particularly the ring-current or Zitterbewegung (zbw) model of the electron. I’ve written many posts about it here — and also tried to help to promote the online “Zitter Institute”, which brings a very interesting group of both amateur and professional researchers together, as well as a rather impressive list of resources and publications which help to make sense of fundamental physics – especially on theories regarding the internal structure of the electron.

The goal — or at least my goal — was (and still is) to clarify what is real and what is not in the quantum-electrodynamic zoo of concepts. That is why I try to go beyond electron models only. I think the electron model is complete as for now: my most-read paper (on a physical interpretation of de Broglie’s matter-wave) settles the question not only for me but, I judge based on its many views, for many others as well. The paper shows how the magnetic moment of the electron, its wavefunction, and the notion of a quantized “packet of energy” can easily be grounded in Maxwell’s equations, special relativity, and geometry. They do not require speculative algebra, nor exotic ontologies.

In that light, I now feel the need to say something — brief, but honest — about where I currently stand in my research journey — which is not on the front burner right now but, yes, I am still thinking about it all. 🙂

On the term “Zitterbewegung” itself

Originally coined by Schrödinger and later mentioned by Dirac, “Zitterbewegung” translates as “trembling motion.” It was meant to capture the high-frequency internal oscillation predicted by Dirac’s wave equation.

But here lies a subtle issue: I no longer find the term entirely satisfying.

I don’t believe the motion is “trembling” in the sense of randomness or jitter. I believe it is geometrically structured, circular, and rooted in the relativistic dynamics of a massless point charge — leading to a quantized angular momentum and magnetic moment. In this view, there is nothing uncertain about it. The electron has an internal clock, not a random twitch.

So while I still value the historical connection, I now prefer to speak more plainly: an electromagnetic model of the electron, based on internal motion and structure, not spooky probabilities.

On tone and openness in scientific dialogue

Recent internal exchanges among fellow researchers have left me with mixed feelings. I remain grateful for the shared curiosity that drew us together, but I was disappointed by the tone taken toward certain outside critiques and tools.

I say this with some personal sensitivity: I still remember the skepticism I faced when I first shared my own interpretations. Papers were turned down not for technical reasons, but because I lacked the “right” institutional pedigree. I had degrees, but no physics PhD. I was an outsider.

Ridicule — especially when directed at dissent or at new voices — leaves a mark. So when I see similar reactions now, I feel compelled to say: we should be better than that.

If we believe in the integrity of our models, we should welcome critique — and rise to the occasion by clarifying, refining, or, if necessary, revising our views. Defensive posturing only weakens our case.

On the use of AI in physics

Some recent comments dismissed AI responses as irrelevant or superficial. I understand the concern. But I also believe this reaction misses the point.

I didn’t try all available platforms, but I did prompt ChatGPT, and — with the right framing — it offered a coherent and balanced answer to the question of the electron’s magnetic moment. Here’s a fragment:

“While the ‘definition’ of the intrinsic magnetic moment may be frame-invariant in the Standard Model, the observable manifestation is not. If the moment arises from internal circular motion (Zitterbewegung), then both radius and frequency are affected by boosts. Therefore, the magnetic moment, like momentum or energy, becomes frame-dependent in its effects.”

The jury is still out, of course. But AI — if guided by reason — might help us unravel what makes sense and what does not.

It is not a substitute for human thinking. But it can reflect it back to us — sometimes more clearly than we’d expect.

A final reflection

I’ll keep my older posts online, including those that reference the Zitter Institute. They reflected what I believed at the time, and I still stand by their substance.

But moving forward, I’ll continue my work independently — still fascinated by the electron, still curious about meaning and structure in quantum mechanics, but less interested in labels, echo chambers, or theoretical tribalism.

As always, I welcome criticism and dialogue. As one business management guru once said:

“None of us is as smart as all of us.” — Kenneth Blanchard

But truth and clarity come first.

— Jean Louis Van Belle

Antimatter, dark matter and cosmogenesis

I used ChatGPT to push the math and logic of my ‘realist’ interpretation of (1) matter-antimatter annihilation and creation (the Dirac and Breit-Wheeler processes, respectively) and (2) dark matter and dark energy to its logical and philosophical limits. For those who do not like to read, I made two short audio videos as well: the one on my “mirror force” idea is here, and from there you can go to the other video(s) in the playlist. 🙂 The implications for cosmogenesis models are rather profound – it calls for another approach to explain any “Big Bang” that may or may not have occurred when our Universe was born – so that is something to explore in the future, perhaps.

A quasi-final proton model?

After a break of a few months, I produced another lengthy video on quantum physics. 40 minutes. Check it out: https://www.youtube.com/watch?v=k_I3Noaup0E. The hypothesis that I, somewhat desperately, advanced in my last paper on the proton model – that the Zitterbewegung model of a proton does not quite look like that of an electron, and that we are probably talking about a “blob” of charge (sphere- or shell-like, or some other “form factor”, perhaps) – makes more sense to me now. I explored it with ChatGPT-4o, and this video is the result. I should immediately that I am immensely impressed with ChatGPT-4o: ChatGPT-3 was not able to really “understand” what I was talking about a year ago or so.

Who knows, perhaps we might imagine other ChatGPT-4o users will take the “dialogue” with AI on these particle models further, and fully develop them not only intuitively but also analytically. As I am currently trying out some AI-powered audio and video applications, I tried Pictory (pictory.ai): I gave it the url of my own long-winding video and it created this video: The proton as a dynamic blob of charge. 100 seconds only instead of 40 minutes. Its contents is, of course, superficial – but I think it is creative and nicely upbeat. I fed both video back to ChatGPT-4o, and it suggested the following refinements if ever I would like to re-do the video(s) – which I am not going to do, but you might like to further explore the remarks it made:

Consistency in Notation and Conventions:
- Ensure that polar and azimuthal angles are consistently defined throughout. Your initial derivations and explanations switched between conventions, potentially confusing viewers about which angle is associated with which base vector.
Tangential Velocity Decomposition:
- The explanation of how the tangential velocity is decomposed into orthogonal components was accurate but could benefit from a clearer mention of why the orthogonality matters in interpreting the motion on the sphere. Adding a visual representation would further clarify the concept.
- The concept of “sloshing” energy between kinetic and electromagnetic forms was well described but could benefit from highlighting the broader implications of this periodic exchange in classical and relativistic oscillators .
Pointlike Charge versus Blob View:
- The transition from discussing a pointlike charge to a “blob” of charge was a major theme but could be expanded by discussing how this shift impacts the assumptions about uniform or non-uniform charge density, as well as its implications for observable properties like the magnetic moment.
The discussion of symmetry along one axis of the double-loop motion was solid but might benefit from more detail on how this symmetry impacts the interpretation of observable properties like the magnetic moment .
Incorporate links to experimental observations, such as the measured magnetic moment and charge radius of the proton, was referenced. Integrating these observations with the theoretical results could be more explicit to strengthen the practical implications .
Visualizations:
- Consider incorporating visualized trajectories (e.g., the double-loop Lissajous pattern), and how they connect to the derived equations and the observed non-constant tangential velocity. This connection will help bridge the abstract mathematics with physical intuition .
Clarifications on Variability:
- The variability of the tangential velocity in the context of symmetry and non-orthogonality in 3D motion, was a key discussion point. Reinforce why this variability does not conflict with the broader relativistic constraints.

So… That’s all folks ! [Looney Tunes.] 🙂

Math and physics: what should you know or learn?

When reading this blog and/or my papers on ResearchGate, you may wonder what kind of mathematical framework you need to appreciate the finer details. We ourselves were asked by fellow proponents of the kind of local and realist interpretation of QM that we are pursuing to look at Clifford or space-time algebra (STA). Well… We looked at it as part of our farewell to this weird pastime of ours, and we documented our response in our very last RG paper on physics, math and (a)symmetries in Nature. If you struggle with the question above, then our answer will probably make you happy: there is no need to learn fancy math to understand easy physics. 🙂

Post scriptum (10 November 2024): As for the “farewell” part of this – I swear – very last paper on all of this weird stuff, it is probably a bit too harsh – but then it is what it is. Let me say a few things about it for the benefit of the would-be student or the starting amateur physicist. Should you study modern physics? I do not think so now, but then I also know that one cannot help oneself when it comes to satisfying some curiosity on fundamental questions. So it probably does not really matter what I advise you to do or not do. I can only say what I write below.

When I started this intellectual journey – what’s this quantum stuff all about? – decades ago, and especially when I got serious about it back in 2013, I had never expected that what happened would happen. No. I’ve always been a good student, and so I expected to sail smoothly through the required math and the intricacies of relativistic mechanics and all of the subtleties of electromagnetic theory – which sort of happened – and, then, to sail through the wonderful world of quantum electrodynamics, quantum field theory and – ultimately – quantum chromodynamics (or let’s call it high-energy physics now) in pretty much the same way.

The latter part did not happen. At each and every page of Feynman’s third volume of Lectures – the ones I was most interested in: on quantum mechanics – I found myself jotting down lots of questions. Questions which took me days, weeks or even years to solve, or not. Most of these questions led me to conclude that a lot of what is there in these Lectures are nothing but sophisms: clever but false arguments aimed at proving the many ad hoc hypotheses that make up the Standard Model. I started to realize the Standard Model is anything but standard: it is just a weird collection of mini-theories that are loosely connected to one another – if connected at all! I started buying more modern textbooks – like Aitchison’s and Hey’s Gauge Theories, which is apparently the standard for grad students in physics – but that did not help. I got stuck in the first chapter already: this Yukawa potential – or the concept of a non-conservative nuclear force itself – did not make sense to me. Not only in an intuitive way: the logic and the math of it does not make sense, either!

Fortunately, I reached out and wrote to non-mainstream researchers whose ideas resonated with me. For example, I will be eternally grateful to Dr. Vassallo for his suggestion to read Paolo Di Sia’s paper on the nuclear force, in which he provides heuristic but good arguments showing the nuclear force might just be a dynamic electromagnetic dipole field. So then I found myself in the business of deconstructing the idea of a strong force. A deeper historical analysis of all these new strange quantum numbers and new quantum conservation laws led to the same: I started looking at sensible suggestions to explain what happens or not in terms of electromagnetic disequilibrium states – developing my own fair share of such suggestions – rather than irrationally or uncritically swallowing the idea of hypothetical sub-nuclear particles on which you then load all kinds of equally hypothetical properties.

While I thought I was doing well in terms of pointing out both the good as well as the bad things in Feynman’s Lectures, I suffered from the weirdest thing ever: censorship on the Internet. Some strange caretaker of Feynman’s intellectual heritage apparently used the weight of his MIT-connection to take down substantial parts of many of my blog posts, accusing me of “unfair use” of this 1963 textbook. Unfair use? Over-use, perhaps, but unfair? All was nicely referenced: when you want to talk about quantum physics, you need some reference textbook, right? And Feynman’s Lectures are – or were, I would say now – the reference then. It was ridiculous. Even more so when he went as far as asking YouTube to strike a video of mine. YouTube complied. I laughed: it took me ten minutes or so to re-edit the video – a chance to finally use all that video editing software I have on my laptop 🙂 – and then put it back online. End of problem.

Case closed? I am not sure. I am a pretty cheerful guy, but I am also quite stubborn when I think something isn’t right. So I just carried on and shrugged it all off thinking this would only boost my readership. It probably did, so: Thank You, Mr. Gottlieb! 🙂 But things like that are hurtful. In any case, that doesn’t matter much. What matters is that things like that do reinforce the rather depressing and very poor perception of academic physics that a Sabine Hossenfelder now (very) loudly talks or – should I say: rants? – about: the King of Science is in deep trouble, and there is no easy way out.

So, what is my conclusion then? I am happy I found the answers I was looking for: there is a logical explanation for everything, and that explanation has been there for about 100 years now: Max Planck, Albert Einstein, H.A. Lorentz, Louis de Broglie, Erwin Schrödinger, Arthur Compton and then some more geniuses of those times have probably said all one can say about it all. And it makes sense. In contrast, I feel the past fifty years of mainstream research were probably nothing more than a huge waste of human intellect. Am I right? Am I wrong? Only the future can tell. To be frank, I am not too worried about it.

I may add one anecdote, perhaps. I did talk to my own son six or seven years ago about what he’d like to study. He was most interested in engineering, but we did talk about the more fundamental study of physics. I told him to surely not study that. In his first year of his Master’s degree, he had to do one course in quantum physics. We walked through it together, and he passed with flying colors. However, he also told me then he now fully understood why I had told him to surely not go for theoretical studies in physics: it just does not make all that much sense. If you would happen to be very young and you want to study something useful, then go for applied science: chemistry, biology or – when you are really smart – engineering or medicine. Something like that. If you want to do physics, go join CERN or something: they probably value engineers or technicians more than theorists there, too! 🙂

Personal note: As for myself, I wanted to study philosophy when I was about 15 years old (so that’s 40 years ago now). I did that eventually, but in evening classes, and only after I did what my good old dad (he died from old age about twenty years ago) then told me to do: study something useful first. I was not all that good with math, so I chose economics. I did not regret that. I even caught up with the math because the math – including statistical modeling! – that you need to understand physics is pretty much what you need in econometric modeling too. So I’ll conclude with a wise saying: all’s well that ends well. 🙂

Using AI for sense-making once more…

As mentioned in my last post, I did a video (YouTube link here) on why I think the invention of new quantum numbers like strangeness, charm and beauty in the 1960s – and their later ontologization as quarks – makes no sense. As usual, I talk too much and the video is rather long-winding. I asked ChatGPT to make a summary of it, and I think it did a rather good job at that. I copy its summary unaltered below.

Beyond the Quark Hypothesis: A Call for Simplicity in High-Energy Physics

1. Introduction: A Personal Journey in Physics

In this video, I reflect on my path as an amateur physicist reaching 50,000 reads—a milestone that underscores both excitement and the challenge of tackling complex quantum theories. Over decades, physics has evolved from classical mechanics to intricate frameworks like quantum field theory and quantum chromodynamics, creating both insight and paradox. This reflection emerges from a deep sense of curiosity, shared by many, to understand not just what the universe is made of but how these theoretical structures genuinely map onto reality.

2. The Crisis of Modern Physics: From Classical Mechanics to the Quark Hypothesis

Moving through physics from classical theories into high-energy particle models reveals a stark contrast: classical mechanics offers clarity and empiricism, while modern particle theories, such as quarks and gluons, often feel abstract and detached from observable reality. The shift to “smoking gun physics”—observing particle jets rather than the particles themselves—highlights a methodological divide. While high-energy collisions produce vivid images and data, we must question whether these indirect observations validate quarks, or merely add complexity to our models.

3. Historical Context: Quantum Numbers and the Evolution of the Standard Model

The 1960s and 70s were pivotal for particle physics, introducing quantum numbers like strangeness, charm, and beauty to account for unexplained phenomena in particle interactions. Figures like Murray Gell-Mann and Richard Feynman attempted to classify particles by assigning these numbers, essentially ad hoc solutions to match data with theoretical expectations. However, as experiments push the boundaries, new data shows that these quantum numbers often fail to predict actual outcomes consistently.

One of the key criticisms of this approach lies in the arbitrary nature of these quantum numbers. When certain decays were unobserved, strangeness was introduced as a “conservation law,” but when that proved insufficient, additional numbers like charm were added. The Standard Model has thus evolved not from fundamental truths, but as a patchwork of hypotheses that struggle to keep pace with experimental findings.

4. The Nobel Prize and the Politics of Scientific Recognition

Scientific recognition, especially through the Nobel Prize, has reinforced certain theories by celebrating theoretical advances sometimes over empirical confirmation. While groundbreaking work should indeed be recognized, the focus on theoretical predictions has, at times, overshadowed the importance of experimental accuracy and reproducibility. This dynamic may have inadvertently constrained the scope of mainstream physics, favoring elaborate but tenuous theories over simpler, empirically grounded explanations.

For example, Nobel Prizes have been awarded to proponents of the quark model and the Higgs boson long before we fully understand these particles’ empirical foundations. In doing so, the scientific community risks prematurely canonizing incomplete or even incorrect theories, making it challenging to revisit or overturn these assumptions without undermining established reputations.

5. Indirect Evidence: The Limits of Particle Accelerators

Particle accelerators, particularly at scales such as CERN’s Large Hadron Collider, have extended our observational reach, yet the evidence remains indirect. High-energy collisions create secondary particles and jets rather than isolated quarks or gluons. In a sense, we are not observing the fundamental particles but rather the “smoking gun” evidence they purportedly leave behind. The data produced are complex patterns and distributions, requiring interpretations laden with theoretical assumptions.

This approach raises a fundamental question: if a theory only survives through indirect evidence, can it be considered complete or even valid? High-energy experiments reveal that the more energy we input, the more complex the decay products become, yet we remain without direct evidence of quarks themselves. This “smoking gun” approach diverges from the empirical rigor demanded in classical physics and undermines the predictive power we might expect from a true theory of fundamental particles.

6. The Particle Zoo: A Growing Complexity

The “particle zoo” has expanded over decades, complicating rather than simplifying our understanding of matter. Initial hopes were that quantum numbers and conservation laws like strangeness would organize particles in a coherent framework, yet the resulting classification scheme has only grown more convoluted. Today, particles such as baryons, mesons, and leptons are grouped by properties derived not from first principles but from empirical fits to data, leading to ad hoc conservation laws that seem arbitrary.

The “strangeness” quantum number, for instance, was initially introduced to prevent certain reactions from occurring. Yet, rare reactions that violate this rule have been observed, suggesting that the rule itself is more of a guideline than a fundamental conservation law. This trend continued with the addition of quantum numbers like charm, beauty, and even bottomness, yet these additions have not resolved the core issue: our inability to explain why certain reactions occur while others do not.

7. Disequilibrium States: Beyond the Particle Concept

One possible perspective is to reclassify many “particles” not as fundamental entities but as disequilibrium states—transient structures that emerge from the interactions of more fundamental components. Viewing particles in this way offers a pathway back to a simpler, more intuitive model, where only stable particles like electrons, protons, and photons are foundational. Such a model could focus on electromagnetic fields and forces, with high-energy states representing temporary disequilibrium configurations rather than new particle species.

This perspective aligns well with the principle of statistical determinism. In the same way that classical oscillators eventually dampen and settle into stable states, high-energy disequilibrium states would be expected to decay, producing stable configurations over time. This model not only reduces the need for numerous quantum numbers but also sidesteps the requirement for exotic forces like the strong and weak nuclear forces, allowing the electromagnetic force to assume a central role.

8. Statistical Determinism and Quantum Reality

Heisenberg and Bohr’s interpretation of quantum mechanics suggests we should accept statistical determinism—systems governed by probabilistic rules where precise knowledge of individual events is inaccessible. This idea does not necessitate mystical randomness but acknowledges our limited ability to track initial conditions in high-energy environments. Probabilities emerge not from an intrinsic unpredictability but from our practical inability to fully specify a system’s state.

From this viewpoint, quarks and gluons, as well as the numerous quantum numbers assigned to unstable particles, are secondary descriptors rather than primary components of nature. Stable particles are the true constants, while all else is a function of high-energy interactions. This interpretation keeps quantum mechanics grounded in empirical reality and sidesteps the need for complex, unverifiable entities.

9. Conclusion: Toward a Pragmatic and Local Realist Approach

This reflection does not dismiss the importance of high-energy physics but advocates a return to fundamental principles. By focusing on empirical evidence, statistical determinism, and electromagnetic interactions, we can build a model that is both pragmatic and intuitive. We need not abandon quantum mechanics, but we should strive to ensure that its interpretations are consistent with the observable universe. Instead of introducing additional quantum numbers or forces, we should ask if these are placeholders for deeper, more coherent explanations yet to be discovered.

The journey of science is, at its core, a journey back to simplicity. If physics is to move forward, it may do so by revisiting foundational assumptions, clarifying what can be empirically tested, and developing a model of matter that resonates with the simplicity we find in classical theories. As research continues, it is this blend of skepticism, open-mindedness, and empirical rigor that will pave the way for meaningful discoveries.

The failure of physics as a science?

It is a coincidence but Sabine Hossenfelder just produced a new video in which she talks once again about the problems of academic physics, while I did what I said what I would not do – and that is to write out why the discovery of new rare kaon decay modes is a problem for the Standard Model. I think the video and the paper complement each other nicely, although Sabine Hossenfelder probably still believes the strong force and weak interactions are, somehow, still real. [I did not read her book, so I don’t know: I probably should buy her book but then one can only read one book at a time, isn’t it?]

The paper (on ResearchGate – as usual: link here) does what Sabine Hossenfelder urges her former colleagues to do: if a hypothesis or an ad hoc theory doesn’t work, then scientists should be open and honest about that and go back to the drawing board. Indeed, in my most-read paper – on de Broglie’s matter-wave – I point out how de Broglie’s original thesis was misinterpreted and how classical quantum theory suddenly makes sense again when acknowledging that mistake: it probably explains why I am getting quite a lot of reads as an amateur physicist. So what’s this new paper of mine all about?

I go back to the original invention of the concept of strangeness, as documented by Richard Feynman in his 1963 Lectures on quantum physics (Vol. III, Chapter 11-5) and show why and how it does not make all that much sense. In fact, I always thought these new quantum conservation laws did not make sense theoretically and that, at best, they were or are what Dr. Kovacs and Dr. Vassallo refer to as phenomenological models rather than sound physical theories (see their chapter on superconductivity in their latest book). However, now it turns out these fancy new concepts do not even do what they are supposed to do, and that is to correctly describe the phenomenology of high-energy particle reactions.

The alternative – a realist interpretation of quantum physics – is there. It is just not mainstream – yet! 🙂

Post scriptum (8 November 2024): For those who do not like to read, you can also watch what I think of my very last video on the same topic: what makes sense and what does not in academic or mainstream physics? Enjoy and, most importantly, do not take things too seriously ! Life family and friends – and work or action-oriented engagement are far more important than personal philosophy or trying to finding truth in science… 🙂

The ultimate proton model?

Today I made a major step towards a very different Zitterbewegung model of a proton. With different, I mean different from the usual toroidal or helical model(s). I had a first version of this paper but the hyperlink gives you the updated paper. The update is small but very important: I checked all the formulas with ChatGPT and, hence, consider that as confirmation that I am on the right track. To my surprise, ChatGPT first fed me the wrong formula for an orbital frequency formula. Because I thought it could not be wrong on such simple matters, I asked it to check and double-check. It came with rather convincing geometrical explanations but I finally found an error in its reasoning, and the old formula from an online engineering textbook turned out to be correct.

In any case, I now have a sparring partner – ChatGPT o1 – to further develop the model that we finally settled on. That is a major breakthrough in this realistic interpretation of quantum theory and particle models that I have been trying to develop: the electron model is fine, and so now all that is left is this proton model. And then, of course, a model for a neutron or the deuteron nucleus. That will probably be a retirement project, or something for my next life. 🙂

Post scriptum: I followed up. “A theory’s value lies in its utility and ability to explain phenomena, regardless of whether it’s mainstream or not.” That’s ChatGPT’s conclusion after various explorations and chats with it over the past few weeks: https://lnkd.in/ekAAbvwc. I think I tried to push its limits when discussing problems in physics, leading it to make a rather remarkable distinction between “it’s” perspective and mine (see point 6 of Annex I of https://lnkd.in/eFVAyHn8), but – frankly – it may have no limits. As far as I can see, ChatGPT-o1 is truly amazing: sheer logic. 🙂 hashtag#AI hashtag#ChatGPT hashtag#theoryofreality

Using AI to solve the 80-year-old problem of the anomaly of the electron magnetic moment?

Pre-scriptum (3 October 2024): I came back from holiday and, because this week-long up and down became quite convoluted, I did what I like to do in a case like that, and that is to take my Bamboo notebook and talk about it all in a video which I added to my Real Quantum Physics channel on YouTube. I also updated my paper on RG: as usual, it went through a few versions, but this one – with a summary co-authored by ChatGTP-4 (and ChatGPT-o1) – should be the final one: enjoy!

Indeed, instead of listening to the international news on the war with Russia and on what is happening in the Middle East (all very depressing), you may want to listen to this and read the latest theory. Perhaps you will be inspired by it to develop your own pet realist theory of what an electron might actually be. I can assure you that it is more fun than trying to understand Feynman diagrams and how QED calculations work. 🙂 But don’t think you will win a Nobel Prize if you do not have the right connections and pedigree and all of that: see this analysis of what makes Nobel Prize winners Nobel Prize winners. 🙂

Original post:

I asked some questions to ChatGPT about my geometric explanation of the anomaly in the electron’s magnetic moment. Here is the chat: https://chatgpt.com/share/66f91760-68b8-8004-8cb2-7d2d3624e0aa. To me, it confirms the ‘explanation’ of mainstream QED makes no sense. We can take Schwinger’s factor and build a series of converging terms using that factor. We can also take my first rough cut at a first-order correction (π(alpha)²/8, see my very early 2019 paper on a classical explanation of the amm), and use that.

You may wonder: why not ask ChatGPT about the best first-order factor to be used here considering the geometry of the situation? The fact is: I did, but the geometry is not all that easy. It first came up with the formula for a spherical cap, but that one does not do the trick. See the latter part of the conversation (link above).

I am on holiday now, and so I will switch off a while but I am thinking AI will do what two generations of ‘new’ quantum physicists did not do: come up with a model that is based on real physics and is easy to understand intuitively. 🙂

PS: Of course, I did another rapid-fire paper on ResearchGate to document it all (the logic step-by-step, so to speak). As the chat is public, feel free to continue the conversation. Note that I used the newest ChatGPT o1 version, now in preview but part of a subscription (which you may not have). Yet again a different beast! The older versions of ChatGPT may not be so smart. This conversation is totally worth the US$20/month I pay for my subscription. 🙂

PS 2: Now that I had it open, I also quickly queried it on my wildest hypothesis: a ‘mirror’ electromagnetic force explaining dark matter and dark energy. While it is totally wild (read: nuts), I entertain it because it does away with the need for an explanation in terms of some cosmological constant. Here is the conversation: https://chatgpt.com/share/66f92c7f-82a0-8004-a226-bde65085f18d. I like it that ChatGPT warns me a bit about privacy. It does look wild. However, it is nice to see how gentle ChatGPT is in pointing out what work needs to be done on a theory in order to make it look somewhat less wild. 🙂

PS 3 (yes, ChatGPT is addictive): I also queried it on the rather puzzling 8π/3 factor in the CODATA formula for the Thomson photon-electron scattering cross-section. See its response to our question in the updated chat: https://chatgpt.com/share/66f91760-68b8-8004-8cb2-7d2d3624e0aa. Just scroll down to the bottom. It took 31 seconds to generate the reply: I would be curious to know if that is just courtesy from ChatGPT (we all like to think our questions are complicated, don’t we?), or if this was effectively the time it needed to go through its knowledge base. Whatever the case might be, we think it is brilliant. 🙂 It is nothing to be afraid of, although I did feel a bit like: what’s left to learn to it but for asking intelligent questions. What if it starts really learning by asking intelligent questions itself to us? I am all ready for it. 🙂