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. 🙂

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.

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:

  1. 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.
  2. 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 .
  3. 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.
  4. 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 .
  5. 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 .
  6. 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 .
  7. 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.] 🙂

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 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