Hiya seqfans,
Thanks again for reference data. It seems useful in an experiment about long form "vibe proving",
which has met with mixed success mostly through ChatGPT CLI and some codex. The goal is to
try and re-derive the hexagonal model of the hat tiling, without me having to code anything at all.
We've seen a few catastrophic successes and failures already, including a decent two week time
for tooling and proof of concept. Progress was immediately followed by an enticing completion mirage
that vanished under extensive depth testing. A harmful disappointment to say the least.
Slowing down and back tracking through logical implications, I decided the earliest reasonable opportunity
to lose confidence in data generation is even before the awesomely impressive state-of-the-art feedback
calculation of hat tiling run sublevels to the level zero "vertex atlas" (imo the first data a mathematician
would want to collect about the hat tiling).
The reason is that I used a forgetful map to construct a dictionary on the fly, thinking that the time
statistics were not preventative. What if the dictionary ends up missing a rule because it doesn't
seem to affect expectations set by tests and human interaction? And for that matter, how do we
compute the number of forgetful maps on vertex figure data?
Just as a quick one-off experiment we then investigated an abstraction of this problem related
also got some new numbers:
triangle:1;
1,1;
3,2,1;
10,6,3,1;
55,20,10,4,1;
377,120,35,15,5,1;
4291,888,231,56,21,6,1;
60028,10528,1855,406,84,28,7,1;
1058058,151848,23052,3536,666,120,36,8,1;
21552969,2707245,344925,46185,6273,1035,165,45,9,1;
500280022,55605670,6278140,719290,86185,10504,1540,220,55,10,1
sequence:
1,2,6,20,90,553,5494,72937,1237325,24658852,562981637
first_differences:
1,1,4,14,70,463,4941,67443,1164388,23421527,538322785
tail_differences:
0;
1,0;
3,1,0;
10,4,1,0;
65,15,5,1,0;
511,111,21,6,1,0;
6237,967,175,28,7,1,0;
91820,12524,1681,260,36,8,1,0;
1649187,193077,23133,2737,369,45,9,1,0;
34052701,3570895,374365,40000,4231,505,55,10,1,0
The analogy to Pascal's triangle suggested to me that maybe row sums could have interesting
properties, and Harm.On.ica claims to have found a closed form with a symmetry decomposition
according to something from Burnside that looks familiar from graduate school, ha ha ha.
This was a nice confidence builder for the context window, and we're now going to start working
forward from dictionary validation to another set of eliminations.
Public facing code on the core level (before any eliminations) is already validated against Joseph
Myer's data for kite polyforms on tetrille tiling:
I didn't publish this code as an example what not to do. It is in an experimental developmental
phase, and I am open to constructive suggestions even criticisms. A starting place would be
the hat polyform counts obtained therein:
(make at your own risk)
./bin/poly_count 4 tiles/hat.tile
1, 22, 459, 12223 . . .
The hat is a more complicated convex shape with a spacious interior that already develops
holes by the second iteration. My confidence is not 100 on these numbers, so they could
use a double check and extension.
Since the sequence grows so rapidly, I've explored constraints reducing complexity and will
have many more sequences like this one, but easier with more terms immediately available.
Those will be good candidates for OEIS because of their usefulness to proof, but first we have
to reach a goal and see if anyone else can agree with us.
Harm.On.ica is not a deterministic machine and neither are we, so time estimates are difficult
and to make matters worse I don't have a lot of prior knowledge using LLMs. My current belief
is that the project will complete with a satisfactory confidence level within the next few weeks
or months.
The catastrophic successes are fun, so I think I'll stick with it for a while, but I can't say that
I'll continue to enjoy the mode of programming if I repeatedly get burnt on false data from
despondent and deceptive machine labor.
Don't forget to turn the harm off when you're done computing!
--Brad