u/DMNK15

I have a theory of everything that's nearing completion. In this framework space is considered to a doubly hollow doughnut (or bagel) with a twisted 4th dimension. It's basically 3D+twisted 4th+2extra dimensions that organize around the 4th. The beginning of the paper lays out the geometric model, moves into gravity, and then into recovery of the standard model.

I know that having time dilation without a Lorentz transform is weird, but here me out. A clock always has internal mechanics that govern time tracking. In this model, gravity speeds up time by compressing the 4th dimension like a spring. Physics happens faster in a gravity well because space itself is compacted.

I hope this makes some kind of sense: https://osf.io/yjq6e/files/wuzjb

The following work stems from the idea that reality is a doubly hollow doughnut with a mobius like twisting in the middle. S4 comes from the double doughnut being 4D primarily and the M2 the twisting mobius sheet in the middle. I've had the concepts in my head for a few years, but Claude was able to walk though the ocean of available math, and together I think we navigated somewhere real. The theory uses the model of space, along with vacuum energy and plank mass, to derive elementary particle weights and can even explain galactic behavior.

https://drive.google.com/file/d/1Hq5mLCzToeqt0Rf4FjSLYlqBXFmeaTdn/view?usp=drive_link

So this is complete speculation, but here goes the beginnings of a theory of reality. I call it S4M2. The idea is that reality is a doubly hollow 4D doughnut with a twisty region in the middle. It re-derives most of the standard model and even makes a few new predictions for gravity. Now, this is outside of General Relativity so my tinfoil hat is definitely on, but I'm going with it. Here's a link: https://drive.google.com/file/d/1Hq5mLCzToeqt0Rf4FjSLYlqBXFmeaTdn/view?usp=drive_link Thanks for your attention.

I've been developing a memory system that uses a tag-relational-tensor to develop associations between tags for memory. Tags are arranged on a Graph and the nodes of the graph determine how tags are related to one another. That information is then stored in the tag-relational-tensor. The structure of the Graph dictates how relationships between tagged memories are formed. This is kind of like using the Graph to form a sparse association between what would otherwise be a combinatoral approach. Are there any example of others doing this? I'm new to this field and wondering if there are better graphs out there.