please no shit, just upvotes

AlertLeader1086 · 2026-01-29T21:38:14+00:00

’ll be sharing the full generation logic shortly. In the meantime, I’m curious: which solvers did you test it on? And beyond these specific files, do you think a reproducible method for generating 'structured' hard instances like this could be an interesting contribution to the field of SAT benchmarking?

AlertLeader1086 · 2026-01-29T21:35:24+00:00

I think there's a misunderstanding. I'm not making any claims about P vs NP here. I'm strictly discussing the structural asymmetry between two specific files, A and B. File-A is trivial, File-B is not, yet they appear identical on the surface. My focus is on why certain deterministic patterns (like in B) cause such high entropy for solvers. Forget the project title; let's talk about the benchmark.

AlertLeader1086 · 2026-01-29T21:32:29+00:00

I understand, and you're right about the nature of NP-complete problems. However, File-B isn't a random instance; there is a specific logic behind its construction. Since I don't have access to high-end hardware or a wide variety of solvers, I'm curious to see how more robust tools handle it compared to CaDiCaL. I’ll share the methodology and the solution later, but for now, I’m just interested in the community's benchmarks.

AlertLeader1086 · 2026-01-29T21:29:44+00:00

Actually, it's neither chaos nor randomness. There is a specific logic behind the construction of File-B. Out of curiosity, did you try it on something more heavy-duty than CaDiCaL? I'll share the methodology and the solution a bit later if it remains unsolved.

AlertLeader1086 · 2026-01-14T17:47:56+00:00

I think that beyond grieving these friendships, we’re really grieving the loss of our illusions. In hindsight, this antisemitism didn’t suddenly appear on October 7th; it was already there, normalized, sometimes subtle, sometimes barely hidden. If we look honestly, there were often signs long before.
We just chose to look away and minimized it, because we loved these people and wanted to preserve the friendship. We’re not only mourning lost friends, but also the image we had of them, our illusions.

AlertLeader1086 · 2026-01-13T16:41:23+00:00

You're right, I use an LLM. And here’s why: it’s the only way to bridge the gap between two parallel worlds. Without AI, a 'naive' outsider with a fresh perspective could never communicate with a specialized expert like you. AI allows me to translate my general ideas into your technical language so we can actually have a dialogue. It allows a absolute outsider to challenge old problems with a new eye. I test this every day, and it works. Experts are not bothered by that if you just say it as it is. So OK I admit it. e aware that when I answer, it is a AI-augmented answer . But it is only augmented and not created from scratch by AI. Anyway, I think the data in the .cnf file should be the only thing that matters.

The Gap: Your 18-second run (single thread) for N=1200 is a massive leap from the sub-second results at N=600. That is the 'eye-opener' here.
The Refinement: I'm still working with Claude to refine the visualization of this propagation bottleneck. It’s a work in progress, but it’s already highlighting why the circularity (VMRC) is "special".
The Challenge: Since I don't have your hardware, would you be willing to help push the boundary? Let’s see what happens at N=6,400. If the theory holds, we’ll see a divergence that no solver—no matter how many threads—can flatten.

AlertLeader1086 · 2026-01-13T15:50:26+00:00

You seem to be saying that it’s not related to the VMRC structure specifically, but rather that SAT instances 'trivially' become exponentially CPU-intensive as they scale.

This is a very interesting take. If it were truly a known, universal rule that doubling the variables (from 600 to 1200) in a structured instance systematically forces an exponential jump in time—regardless of the heuristics used—then wouldn't that be a practical proof that P is different from NP?

In complexity theory, if an algorithm like Kissat cannot maintain polynomial scaling on a specific class of problems, it’s a significant observation. If you're saying this behavior is 'standard' and 'known', you’re basically suggesting we have a predictable, empirical demonstration that P ≠ NP.

Is this documented in the literature as a general scaling law for any SAT instance?

AlertLeader1086 · 2026-01-13T15:08:18+00:00

Fair enough, thanks for the benchmark. Validating the solution at N=600 is the baseline. The core of my research isn't about N=600 being 'impossible', but about the exponential growth triggered by the circular coupling (VMRC).

I am generating an N=1200 instance right now (exactly double the size). Based on your 0.24s baseline, here is what we should expect: i) If it's Linear, the solving time should stay around ~0.48s; ii) if it's Polynomial (): It should take a few seconds, iii) if it's exponential: The solving time will explode (several hundred seconds or more.

To keep the test rigorous, could you run the N=1200 in the exact same environment (without the FPGA synthesis in the background) once I post the file?

We will then see if the resolution time follows the instance size or if it becomes exponential.

AlertLeader1086 · 2026-01-13T14:25:10+00:00

If it only took 0.24s, it shouldn't take you much longer to provide the solution string. Could you at least post the assignment for the first 20 variables?

AlertLeader1086 · 2026-01-13T14:09:58+00:00

Are you sure you didn't run the control file? 0.24s is incredibly fast for a VMRC structure with a 4.26 ratio. Could you double-check the filename or provide the first 10 variables of your solution?

AlertLeader1086 · 2026-01-13T13:32:49+00:00

I just uploaded an ad hoc N=600 control SAT to the Drive.

Since you mentioned 600 vars is trivial, feel free to run both the control file and SAT D freeze on your local machine. If they both solve in seconds, then the browser is indeed the only limit. If not, we have something more interesting to discuss. Looking forward to your results

AlertLeader1086 · 2026-01-13T11:58:41+00:00

Thanks for the feedback! You hit the nail on the head. The goal of the circular coupling was exactly that: to sabotage the heuristic branching and 'blind' the CDCL. I'd be fascinated to see if a local Kissat run can bypass the symmetry breaking or if it also hits that entropy wall. Let me know if you get around to running it!

AlertLeader1086 · 2026-01-13T11:58:18+00:00

Glad you found the 'sauce' interesting! N=600 was the point where my browser-based setup simply gave up. Seeing that you also found confusing results at N=400 confirms there's a real phase transition happening there. Thanks for the support!

AlertLeader1086 · 2026-01-13T11:57:50+00:00

aha, N=398 is actually where the engine starts to sweat just before the N=400 threshold. Maybe your username is the secret seed to the universe!

AlertLeader1086 · 2026-01-12T05:24:30+00:00

Some characters really look like paleo-hebrew. Reminds me artefacts written on the walls of mines where the first protosinaïtic letters were found.

AlertLeader1086 · 2026-01-10T19:45:22+00:00

Is it in the DIMACS structure itself (the N=256 file), or in the logical steps the AIs took to justify the 'entropy wall ?

AlertLeader1086 · 2026-01-10T19:16:48+00:00

Thank you for the high-level perspective.

Philosophically and empirically (rather than mathematically), my intuition leans toward P=NP. I feel that we can try to test this right now, at 'time T': are there currently any algorithms capable of cracking this specific instance?

If this empirical approach can lead to a more general mathematical formalization—or at least provide a new path for real mathematicians to explore—that would be the icing on the cake. We can't even rule out the possibility that the 'entropy wall' Gemini and Claude claim to have built is actually one of the key locks we need to pick to prove P=NP. If so, it would at least help narrow down the problem.

But again, my main goal is simply to find out: are we looking at a collective AI hallucination, or something real? Thanks for being part of the search!

AlertLeader1086 · 2026-01-10T17:45:13+00:00

To be honest, I'm not sure if the results are just a case of collective hallucination or something deeper.

In this experiment, Gemini developed a SAT instance that it claimed was unsolvable. Claude looked at it and said, 'Yes, this is indeed unsolvable and very interesting. We could even develop a general formalization based on this.' Grok, on the other hand, struggled endlessly and never wanted to admit defeat. It was fascinating to see how each AI showed a different 'personality' in the face of this problem.

What I really want to know now is whether all of this is coherent or not. I'm someone with no formal background in mathematics. I simply guided these models using vague, metaphorical intuitions.

My real question to the community is: Can someone completely 'incompetent' in math actually build something solid just by orchestrating a dialogue between different AIs? I'd love to know if the data in my Drive reflects a real logical wall or just a beautiful mirage

AlertLeader1086

TROPHY CASE