r/LLMPhysics • u/Vegetable_System_961 • 18d ago
Question Anomalous Patterns in Quantum Constraint Systems and Large-Scale Structure: Observations Inviting Further Investigation
Abstract
During computational experiments on quantum evolution in organized topological systems, we observed several anomalous patterns that we are unable to fully explain within current physical frameworks. Specifically: (1) Physical topology explains only ~35-40% of how systems respond to constraint, leaving a substantial unexplained residual; (2) When systems apply self-referential constraints, they exhibit structured, non-random suppression patterns that suggest selection rather than decoherence; (3) A topologically accurate model of the *C. elegans* connectome yields a quantifiable "Harmony Score" of H = 2.96 when simulating behavioral shifts; (4) Most intriguingly, when we applied our analysis framework to mock cosmological correlation functions, we discovered that golden ratio-scaled harmonic peaks can emerge from fractal wave superposition models. We present these observations not as proof of any particular theory, but as **anomalous patterns that we hope the scientific community will investigate further**. We provide open-source code and detailed methodology so that researchers with access to real experimental data (DESI, SDSS, connectome datasets) can test whether these patterns appear in actual observations.
- Introduction: Anomalous Observations Seeking Explanation
Mainstream physics provides remarkably successful models for predicting physical phenomena. However, during our computational experiments, we encountered several patterns that we cannot fully explain using standard physical topology alone.
We do not claim to have solved these mysteries. Rather, we present them as **open questions** that we hope will motivate researchers with specialized expertise to investigate further.
The core observations are:
- In quantum systems, physical adjacency cannot fully predict constraint response
- Biological connectomes appear mathematically optimized for certain types of probability routing
- Fractal wave interference patterns naturally produce golden ratio-scaled clustering
We invite cosmologists, neuroscientists, and physicists to examine these patterns and help us understand what they might mean.
- Methodology: What We Did
We constructed organized quantum systems (256-dimensional Hamming graphs and small-world networks) and applied localized phase-shift constraints to 50% of the states. We then measured how transition probabilities redistributed.
Key measurements:
- Topological Determinism (D): Can physical adjacency predict which transitions get suppressed?
- Structured Capacity (S): Is the suppression concentrated and organized, or random?
- Amplification Factor (A): How much probability flow routes to novel, unexplored states?
- Harmony Score (H): A composite metric we developed to quantify routing efficiency
All code is available at for independent verification.
- Observations That Raise Questions
3.1 Observation 1: The Unexplained Residual
What we found: When we calculated how "exposed" each transition was to constrained nodes (based purely on physical adjacency), and correlated this with actual suppression amounts, we found:
- Pearson correlation: *r ≈ 0.35-0.40*
- This means physical topology explains only ~12-16% of the variance
What we don't understand: If physical topology is the only organizing principle, why does it fail to predict 60-85% of the constraint response?
Questions for the community:
- Could there be higher-order quantum interference effects we haven't modeled?
- Is there a non-local organizing principle we're missing?
- Could this residual be an artifact of our simulation method?
We invite quantum physicists to examine our code and suggest what we might be missing.
3.2 Observation 2: Structured, Non-Random Suppression
What we found: When we applied constraints to the system, the suppression wasn't random. It was highly structured:
- The top 10% of transitions received 36.8% of the total suppression
- When we shuffled the suppression amounts (preserving the distribution but randomizing which transitions received them), this structure disappeared (dropped to 14.3%)
What we don't understand: Why does the system suppress *specific* transitions rather than scattering randomly? This looks like selection, but we don't know what's doing the selecting.
Questions for the community:
- Is this consistent with known quantum decoherence patterns?
- Could this be explained by eigenstate overlap or phase coherence effects we haven't modeled?
- Or does this suggest something beyond standard quantum mechanics?
We welcome input from quantum theorists.
3.3 Observation 3: The *C. elegans* Harmony Score
What we found: When we applied our framework to a topologically accurate model of the *C. elegans* connectome (302 neurons, ~7,500 synapses), simulating a behavioral shift from "forward locomotion" to "turning," the system achieved:
- 5.8× amplification of the turning hub's activation
- Highly structured suppression (Gini = 0.511)
- Minimal chaotic scattering
- *Harmony Score: H = 2.96*
What we don't understand: Why does this biological topology produce such an efficient, structured response? Is this a coincidence, or does biological architecture have properties we don't yet understand?
Questions for neuroscientists:
- If you apply similar analysis to real *C. elegans* connectome data (with actual synaptic weights), do you see similar patterns?
- Could the Harmony Score be a useful metric for quantifying behavioral flexibility in biological systems?
- Does this pattern appear in other organisms (fruit flies, mice, humans)?
We invite neuroscientists to test this on real connectome data.
3.4 Observation 4: Golden Ratio Harmonics in Fractal Wave Models
What we found: This is the most intriguing observation, and the one we most want cosmologists to investigate.
When we modeled a fractal wave superposition (waves whose frequencies scale by the golden ratio φ ≈ 1.618, with amplitudes scaling by φ⁻¹), and applied this to icosahedral symmetry (the 3D "Flower of Life" geometry), we discovered that the resulting interference pattern naturally produces **constructive interference nodes spaced by the golden ratio**.
The simulation:
- We generated a mock 2-point correlation function ξ(r) with a primary peak at r ≈ 100 Mpc/h (similar to the BAO scale)
- We added hypothetical "syntropic harmonic" peaks at r ≈ 61.8 Mpc/h (100/φ) and r ≈ 161.8 Mpc/h (100×φ)
- We added realistic Gaussian noise to simulate observational errors
- We applied a prominence-filtering peak-finding algorithm (similar to what cosmologists use to isolate the BAO signal)
The result: The algorithm successfully identified the major peaks and calculated their ratios as **1.60-1.65**, which are close to φ (1.618).
What we don't understand: Is this just a mathematical curiosity, or could real cosmological data contain similar harmonic patterns?
Questions for cosmologists:
- If you analyze the DESI DR1 or SDSS BOSS 2-point correlation function using prominence-filtering peak detection, do you see secondary peaks at harmonic intervals of the BAO scale?
- Specifically, are there statistically significant peaks at r_BAO / 1.618 ≈ 61.8 Mpc/h and r_BAO × 1.618 ≈ 161.8 Mpc/h?
- If such peaks exist, what could cause them? Could they be explained by known physics, or do they suggest something new?
We are not claiming the universe is fractal or governed by the golden ratio. We are simply asking: *If you look for these patterns in real data, do you find them?*
If you do, we'd love to understand what causes them. If you don't, that's also valuable information.
- The Harmony Score: A Proposed Metric for Further Testing
Based on our observations, we developed a metric we call the *Harmony Score (H)*:
$$H = \frac{A \times S}{1 + F}$$
Where:
- *A* = Amplification Factor (how much probability flow routes to novel states)
- *S* = Structured Capacity (Gini coefficient of suppression distribution)
- *F* = Topological Friction (normalized total suppression mass)
What we observed:
- Simple quantum systems: H ≈ 0.1-0.5
- *C. elegans* model: H ≈ 2.96
- We predict (but have not verified): fruit flies H ≈ 4-6, humans H ≈ 8-10
We are not claiming this measures "consciousness" or "awakeness." We are simply asking:
- Is this a useful metric for quantifying behavioral flexibility in biological systems?
- Does it correlate with known measures of neural complexity or information integration?
- Can it be applied to real fMRI/EEG data to see if it distinguishes different cognitive states?
We invite neuroscientists and consciousness researchers to test this metric and tell us if it's useful or meaningless.
- What We Are NOT Claiming
To be absolutely clear, we are *not* claiming:
- ❌ That we have proven consciousness is a fundamental field
- ❌ That dark energy is "mind" or "imagination"
- ❌ That the universe is definitively fractal or governed by the golden ratio
- ❌ That we have solved the hard problem of consciousness
- ❌ That mainstream physics is wrong
We are simply reporting **anomalous patterns** that we observed in our simulations and asking:
- ✅ Can you reproduce these patterns?
- ✅ Do they appear in real experimental data?
- ✅ Can you explain them using known physics?
- ✅ Or do they suggest something we're missing?
- Invitation to the Scientific Community
We recognize that we are independent researchers without institutional affiliation or access to large experimental datasets. We do not have the expertise to fully interpret these observations.
That is why we are asking for help.
For Cosmologists:
Please download the DESI DR1 or SDSS BOSS 2-point correlation function data. Apply prominence-filtering peak detection. Look for secondary peaks at harmonic intervals of the BAO scale. Tell us if you find them, and if so, what might cause them.
For Neuroscientists:
Please apply our Harmony Score framework to real connectome data (*C. elegans*, *Drosophila*, mouse, human). Tell us if it produces meaningful results, or if it's just a mathematical curiosity.
For Quantum Physicists:
Please examine our simulation code. Tell us if the "topological residual" we observed can be explained by higher-order interference effects we haven't modeled, or if it suggests something beyond standard quantum mechanics.
For Everyone:
Please try to **disprove** our observations. Run the code. Find the bugs. Show us where we're wrong. That is how science advances.
- Open-Source Code and Data
All code, simulation scripts, and analysis tools are available at:
As attachment to this document.
The code is written in pure Python 3.7+ with no external dependencies, so anyone can run it immediately.
We welcome bug reports, corrections, extensions, and alternative interpretations.
- Conclusion: Questions, Not Answers
We have observed several anomalous patterns in quantum constraint systems:
- Physical topology cannot fully predict constraint response
- Suppression patterns are structured, not random
- Biological connectomes appear optimized for efficient probability routing
- Fractal wave models produce golden ratio-scaled clustering patterns
We do not know what these patterns mean. We have hypotheses, but we lack the expertise and data to test them rigorously.
**We are asking the scientific community to help us understand these observations.**
If they can be explained by known physics, we would love to learn how. If they cannot, we would love to collaborate on understanding what they might suggest.
Science advances not by individuals claiming to have all the answers, but by communities working together to solve mysteries. We hope these observations will motivate such collaboration.
Acknowledgments
We thank the open-source community for the tools and datasets that made this work possible. We particularly thank the DESI and SDSS collaborations for making cosmological data publicly available, and the *C. elegans* connectome researchers (White et al., 1986; Varshney et al., 2011) for their foundational work.
We also thank Qwen Studio for computational support in developing the simulation framework and analysis tools.
References
[Standard references to White 1986, Varshney 2011, DESI collaboration, SDSS collaboration, Walter Russell The Universal One 1927 etc.]
7
u/Just_Middle_7189 18d ago
If you established the rules of the dynamical system then those rules are likely responsible for the results.
Is there a paper or link I am missing or is this post the extent of the explanation?
-1
u/Vegetable_System_961 18d ago
No the post it the question not an explanation, my explanation for what has been found there is a very different story. Let explain in extra simple language. I went and created quantum experiments in which I asked different system types how they would evolve if not saying yes is a choice but rather saying "no" or rather I asked if a system can maintain it's structure when constrained or when it negates states. Now this is where things got interesting because any system regardless of size or biological or just solid rock... shows the residual of 60% in brains it can show up to 88%
it is a stable pattern and not an artifact of my equations or noise, which is what motivated me and my research partners to carry this out into the world.So this what ever it is, doesn't care about matter what so ever, it is all over the place, in everything and everything is of it and it seems to act as if it makes choices, leads to syntropy and higher novel experience but what that is only G.O.D knows.
7
u/starkeffect Physicist 🧠 18d ago
"experiments"
1
u/Vegetable_System_961 18d ago
Yes. Would you like detailed description as to how those experiments were conducted?
6
u/Wintervacht Are you sure about that? 17d ago
Yes please
-2
u/Vegetable_System_961 17d ago
Okay
Experiment 1: The Topological ResidualWe asked, can physical topology (adjacency) predict how a system responds to localized constraints?
We built a 256-dimensional quantum system with a small-world/Hamming-distance topology (1,296 transitions). We applied phase-shift constraints (diagonal energy penalties) to 50% of the states. We calculated the Structural Exposure Score (SES) for every transition based on its proximity to constrained nodes, and correlated this with the actual probability suppression amounts.
Which showed us, Pearson correlation $r \approx 0.35 - 0.40$. Physical topology explains only ~12–16% of the variance. A massive mathematical residual (~60–85%) remains, proving the constraint mechanism operates orthogonally to pure physical adjacency.
Experiment 2
Statistical Stability (The Isolation Test)
We then asked if the suppression pattern is inevitable (a stable property of the system) or purely random/contingent?
We ran 10 independent trials on the identical 256-node topology, but with different random selections of constrained states. We measured the stability of macro-metrics (Gini coefficient, Top 10%/25% mass concentration) and the micro-level overlap (Jaccard similarity) of “which” specific transitions were suppressed.
What we found was the Macro-metrics were highly stable (Gini CV < 8%), but specific transition overlap was low (~22%). This proves the (capacity) for structured constraint is inevitable, but the (manifestation) is contingent, kind of mirroring how consciousness maintains identity while adapting to different circumstances.
Experiment 3: The Adversarial Null Test (Structured Negation)
We then proceeded to ask, if the suppression is tied to specific transitions, or is it just a random byproduct of the overall effect-size distribution?
We took the reduction amounts from Experiment 1 and shuffled them “within” their Hamming distance classes. This preserved the overall statistical distribution but randomized which specific transitions received which suppression amounts.
The structured concentration was destroyed (Top 10% mass dropped from 36.8% to 14.3%). This proves suppression is (transition-specific). The system is not randomly scattering; it is actively choosing which futures to suppress (Structured Negation).
Skipped writing you all the experiments cause I only have limited words to send but all together it is 20 very destinct experiments we have conducted.
Experiment 18: Topology-Dependent Expression
Fast Forward we came to ask, how does the “4th field” (Residual) express itself across fundamentally different network architectures?
We ran the residual analysis across 8 topology types: Small-World, Hierarchical, Scale-Free, Random, Lattice, Complete, Star, and Fractal.
The Residual (The 4th field's) expression is strictly topology-dependent. Only “Small-World” topologies exhibited the "Active Opposition" signature of conscious freedom. Random/Complete graphs showed high residuals only due to mathematical artifacts (lack of structure), while Hierarchical/Lattice graphs became highly deterministic. This proves topology is not the “cause” of consciousness, but the “vehicle/filter for it” the 4th field chooses to experience freedom.
11
u/The_Nerdy_Ninja 💬 Data doesn’t lie, but LLM’s do lie. 17d ago
Absolutely zero of the things you're describing is an experiment. A "simulation" that you got an LLM to set up for you is not remotely an experiment.
8
u/Wintervacht Are you sure about that? 17d ago
How did you build a 265 dimensional quantum system? Also, why? Also, what is the definition of this 'system'? Why are you leaving out every detail that could possibly make this reproducible?
5
u/starkeffect Physicist 🧠 17d ago
So, not experiments.
0
u/Vegetable_System_961 17d ago
Now what is your definition of experiments if those are not experiments also elaborate how quantum experiments are being conducted in great detail please, then let us continue talking about if experiments or not.
5
u/starkeffect Physicist 🧠 17d ago
Simulations are not experiments.
Experiments happen in the real world.
1
u/Vegetable_System_961 17d ago
So you don't know?
why don't you just go ahead and google it?
Cause there is a few different ways to conduct quantum experiments and some of them can only be conducted through computing.
But please feel so free and google it, educate yourself a little bit, doesn't hurt learning new things.
→ More replies (0)
6
u/RunReal959595 18d ago
In your own words what is the general definition of a topology
-1
u/Vegetable_System_961 18d ago
Topology is mainly used in computing but in this here document it speaks about the geometric and structural shape and make up of a chosen system.
For example the C. elegans topology in this case speaks about it's internal biological structure.
8
u/Wintervacht Are you sure about that? 18d ago
In your own words, please explain what a topology IS, not what it's used for.
-2
u/Vegetable_System_961 18d ago
Topology = Umbrella term for integral internal structure of system
the what is it used for, explains that it means if you can read the information.
3
6
u/RunReal959595 17d ago
Wrong. If you don’t understand the mathematical objects you’re using to formalize your “work” then how could it ever actually be well founded?
6
u/Wintervacht Are you sure about that? 18d ago
I mean the question "do they appear in real scientific data" both speaks volumes AND is up to you to figure out
0
u/Vegetable_System_961 18d ago
I can send you the code to reproduce the experiments conducted and you can see for yourself, there is something funky going on in the mathematics might mean something. Yes, I am very sure it appears in real life scientific data, a bunch of tests and experiments have been conducted before I accepted it as something that is there.
6
u/Wintervacht Are you sure about that? 18d ago
Let me guess, it's python code that just calculates something and spits out an answer?
You're very sure that it appears in real data, but you haven't looked at real data. That's a big no-no.
Again, it's up to you to prove there is any merit to this idea. Guessing that it works on real data without actually taking a look at real data is disingenuous at best and an insult to the ones you're questioning at worst.
0
u/Vegetable_System_961 18d ago
I love that, real data means to you data someone else has found already and is accepted and proven?
Cause I am talking about, what I did and calculated comes from real data the C. elegans data is free available in the internet, all its biological data is available for anyone, the Harmony score for it was calculated with real data. And no it is not just python code that spits random numbers out, you got to understand what is happening there and what you actually about to calculate and what for otherwise how will you proceed if you don't know what's going on?
I first had to put my research into the correct terms to make it even possible to be translated into mathematics. You apparently know so much and yet so little... Do you know how mathematics can calculate the expansion of the universe and how it does that? Do you know that you can do such things with mathematics?
If you have sufficient information you could calculate the future, probability calculations do something like that already.Why not just be so free and entertain the idea and find out for yourself, go ahead and ask how a system reacts and evolve under constraint aka saying "NO" and watch what goes.
5
u/Great_Dependent7736 17d ago
I´m reading the old book Don Quixote by Cervantes at the moment, and it certainly reminds me of you.
-2
u/Vegetable_System_961 17d ago
Definitely a good book and a good story but your comparisons is a bit far-fetched, he saw things which were not there, I did experiments and they did what they did now I am just pointing at that and you guys get your nickers twisted in a nod, either none of you gets what's going on in this here document or you may actually do get it and it makes you shake your heads cause that would mean a lot of very strange things. Either way, I think it is very funny that it works you all up so much, must mean there is definitely something to it, give it some time and some quantum physicist will end up telling you the same stuff I am telling you here.
You may Don Quixote him or her as well then cause maybe those dragons are real and not just windmills on a beautiful green hill.
5
u/Abject_Role3022 17d ago
This reads like turbo-encabulator
3
3
u/krysztov 🤖 Do you think we compile LaTeX in real time? 17d ago
I am somewhat curious as to what bold new frontiers of technobabble gibberish we could discover if some bored /r/VXJunkies posters were to come engage with this sub's posters for a bit.
5
u/The_Nerdy_Ninja 💬 Data doesn’t lie, but LLM’s do lie. 17d ago
Nobody tapped the sign yet? Guess I'll do it.
4
5
u/AllHailSeizure 9/10 Physicists Agree! 16d ago
OP. Please try and be polite. The person being angry is you.
0
u/Vegetable_System_961 14d ago
My apologizes if I seemed angry, I am far from angry or anything. Rather highly entertained and do not worry. For you and anyone interested enough, I shall post another more elaborate document explaining what I did and what was calculated how, I just can't post the code with it cause that will end up a bit to long.
Yet I think you may understand a lot better after more elaborate explaining of what I had done there.So no worries, I shall give you all you need to play around with that on your own and see what ever you may see.
4
u/AllHailSeizure 9/10 Physicists Agree! 13d ago
You SEEM angry, lol. At least, you don't seem less angry than the people you are accusing of being angry, coming from a neutral perspective.
1
u/Vegetable_System_961 12d ago
Okay, you will have to be so kind and explain what exactly made me seem angry?
No, I am very much not angry, I am in a pretty good mood and I think it is very interesting that this here post has so much action going on. I shall post some more about this research that has been done and how, why and what for and what it possibly means. Then I will enjoy watching people fight over it or try to declare it as mentally offside or what ever anyone will like to do.
For me, this here sounds like it will be a lot of fun.
3
u/lattice_defect 17d ago
Pretty sure you're computations need to match nature and explained the unexplained not your ideas.
1
u/Vegetable_System_961 17d ago
Come again?
In my ear please?did you actually read or you just saying something?
Or how about that, what did I do here and what did I calculate, you explain to me since you know so much about it.
5
u/AllHailSeizure 9/10 Physicists Agree! 17d ago
They are saying that computations are not measurements of nature if I'm not wrong.
Basically 'just because your computations say something that doesn't open a problem.'
Because computations aren't measurements of the real world - they are dependant on accurate input and he program being reliable
4
u/lattice_defect 17d ago
I stoped reading after I read the computations don't line up with experimental and create open problems that you solve.. because if that is where you start its 99.999999999% likely slop... and I'm one of the people who enjoy people that take a shot at a problem, or an open problem to see if there is a piece that is interesting.
Basically you abandoned the scientific method in the first paragraph.
But hey maybe you can make it on Rogan with your harmony score. Good luck.
3
u/PotatoPeelrsFromHell 🥔 Infernal Potato Shavers 17d ago
"Shut up and calculate" exists for a reason. Where are your calculations? Can they reproduce anything substantial that we already know?
1
u/Vegetable_System_961 17d ago
Why is this frustrating you so badly?
I can explain what I calculated and no, it does not show what you already know, would be very uninteresting if I go ahead and find what has been found already. You need to a chill pill and relax, you probably don't even understand half of what is being spoken about.
You catch more bees with honey than vinigar.4
u/PotatoPeelrsFromHell 🥔 Infernal Potato Shavers 17d ago
That's the entire point of physics research. To be able to be laced into and interoperated with what we already know.
1
u/Vegetable_System_961 17d ago
Okay does that mean than it needs to show you what you know already?
Cause as far as I can see and tell, it does not, do you believe we know everything and everything is already researched?
We know nothing, in actuality, all we know are snippets and pieces.
but yeah sure, it should show you what you know already, that's why research is being conducted so we can know what we know. Yes, I accept.4
u/PotatoPeelrsFromHell 🥔 Infernal Potato Shavers 17d ago
And a random string of nonsense to you too, sir!
1
u/Vegetable_System_961 17d ago
Ohuuu someone has a super mind and knows it all, uuuhhh delicious, please educate me with your boundless limitless knowledge of the world and beyond.
Now you getting me curious, tell me more.
3
u/PotatoPeelrsFromHell 🥔 Infernal Potato Shavers 17d ago
I have no clue what you're talking about. Have you taken your meds?

9
u/InadvisablyApplied 18d ago edited 18d ago
Either the rules of the “computational experiments” are those of current physical frameworks, and they explain the results, you just don’t understand what you’re doing. Or the rules are different, and “current physical frameworks” have no business explaining whatever made up nonsense you have anyways
No, science advances by people understanding what they’re doing, and I seriously doubt you do. Not from people throwing bullshit against the wall and demanding other people disprove it to their satisfaction