OMG, where was this article when I was first learning about tensor products?

https://www.math3ma.com/blog/the-tensor-product-demystified

In 10 minutes I learned more about tensor products than I did in grad school. In particular, I see more of the connection between the way math uses tensor products and how physicist types think of them, as higher-dimensional matrices.

This kind of thing really riles me up. It's the kind of thing that makes me want to go back to teaching, because it hits the exact personality/psychological trait that makes me like teaching: I learn about some cool math thing and I want to charge into a classroom and say "GUYS! I just figured this out! It's so cool and interesting! OMG tensor products are the best, let me show you why!"

It bothers me that I was taught about tensor products in such a bad way. I want students to get something better than I did.

(OTOH, maybe I'm just not very smart, or was a bad student. That's a real possibility. But how great would it be for even dim bulbs and lazy students to get *something* out of learning about a topic?)

#math #linearalgebra #mtbos #teaching

The Tensor Product, Demystified

@ddrake Took me (many) years after graduating before a random comment by @johncarlosbaez made me finally understand what a tensor actually is. All the explanations I got as a student were so needlessly convoluted that nothing sticked with me.

@j_bertolotti - thanks, Jacob! I agree that tensors are often explained badly. And I agree with @ddrake that Tai-Danae Bradley's blog explanation is delightfully clear.

I learned tensors because I wanted to understand general relativity and this was a bridge I *had* to cross. So I spent a lot of time studying them. Nowadays Google's open-source machine learning software "TensorFlow" may push other people into understanding tensors. But it would be nice if people got a tiny taste of them right around when learning matrices.

Like: "Hey! It's cool how you can multiply a vector by a 2-dimensional array of numbers and get a vector. But it doesn't stop there! In a viscous fluid the stress is a 2d array of numbers and so is the gradient of velocity, and you have to multiply the gradient of the velocity by a 4-dimensional array of numbers to get the stress!"

Well, that's probably too intense, but just some hint that after Tᵢⱼ thingies we'll want Tᵢⱼₖ thingies and Tᵢⱼₖₗ thingies and so on...

https://en.wikipedia.org/wiki/Viscosity#General_definition

Viscosity - Wikipedia

@johncarlosbaez @j_bertolotti @ddrake I always understood them from the algebraic perspective, as the most general way to multiply vectors. This explains everything else about tensors so nicely!

@lisyarus @j_bertolotti @ddrake - I probably started by understanding tensors from the physics perspective, where a rank-n tensor is a gadget that describes some numerical quantity that depends linearly on n different vectors. I might have seen them first in the Feynman Lectures.

Then we can refine this by distinguishing vectors from covectors. Then I learned about tensor products of vector spaces, and it became clear that the physicists' tensors are elements of V āŠ— ... āŠ— V āŠ— V* āŠ— ... āŠ— V*. This is what you learn in a math class, but also if you read a decent book on general relativity.

@johncarlosbaez @j_bertolotti @ddrake I came to an understanding through tensorflow. I wish I had had more of a mathematical exposure to them first, though.

@j_bertolotti I had the same thing happen with real analysis. I took it in undergrad, in grad school, and was always..."meh". But years later, after teaching basic stuff, and encountering little things about real analysis here and there, I came around to the "OMG, guys, this is amazing!" attitude.

Just like with the tensor product stuff that I started with here, I want to go back and teach real analysis, so that I can burst into a classroom and say, "guys! This amazing! The real numbers, and functions thereof, are SUPER WEIRD and amazing!"