- #1

Vanilla Gorilla

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- TL;DR Summary
- My question is just if the points are correct and true statements; if not, how could I rewrite them? :)

Some people like to write tensor products as 3d arrays, but that inherently means we lose information when compared to the 2D representation

That’s because in the 2D representation, we see this is a (1,2)-tensor, because there's 1 column aspect and 2 row aspects.

A (m,n) tensor can be represented by m column aspects and n row aspects, when converted to array form.

So, I've been watching eigenchris's video series "Tensors for Beginners" on YouTube. I am currently on video 14. I, in the position of a complete beginner, am taking notes on it, and I just wanted to make sure I wasn't misinterpreting anything.

At about 5:50, he states that "The array for Q is a row of rows of columns. And some people like to think that since there are three parts in this tensor, they think that we should visualize this tensor array instead as a 3d cube, like over here. But I don't like to do that. Because when we visualize it this way, we lose out on how many vector parts and how many covector parts there are. And we sort of lose information about what type of tensor This is. But when I write the tensor out like this as a row of rows of columns, I can still see by looking at this, that this is a (1,2)-tensor, because there's one column aspect and two row aspects."

Regarding this, I interpreted it to imply the points below.

My question is just if the points are correct and true statements; if not, how could I rewrite them? :)

P.S., I'm not always great at articulating my thoughts, so my apologies if this question isn't clear.

P.P.S., I know this isn't high school material, but I am currently in high school, which is why I made my level "Basic/high school level"

At about 5:50, he states that "The array for Q is a row of rows of columns. And some people like to think that since there are three parts in this tensor, they think that we should visualize this tensor array instead as a 3d cube, like over here. But I don't like to do that. Because when we visualize it this way, we lose out on how many vector parts and how many covector parts there are. And we sort of lose information about what type of tensor This is. But when I write the tensor out like this as a row of rows of columns, I can still see by looking at this, that this is a (1,2)-tensor, because there's one column aspect and two row aspects."

Regarding this, I interpreted it to imply the points below.

My question is just if the points are correct and true statements; if not, how could I rewrite them? :)

- Some people like to write tensor products as 3d arrays, but that inherently means we lose information when compared to the 2D representation
- A (m,n) tensor can be represented by m column aspects and n row aspects, when converted to array form.

P.S., I'm not always great at articulating my thoughts, so my apologies if this question isn't clear.

P.P.S., I know this isn't high school material, but I am currently in high school, which is why I made my level "Basic/high school level"