There are at least three distinct conceptual roles which vectors and vector spaces play in mathematics:
- A vector is a column of numbers. This is the way vector spaces appear in quantum mechanics, sections of line bundles, elementary linear algebra, etc.
- A vector is a weighted direction in space. Vector spaces of this kind are often the infinitesimal data of some global structure, such as tangent spaces to manifolds, Lie algebras of Lie groups, and so on.
- A vector is an element of a module over the base ring/field.
Let’s take an example that you’re familiar with, vector spaces, and generalize it to get some intuition for working with modules.
Fields $\hookrightarrow$ Rings
If $K$ is a field, then a $K$-vector space (a vector space over $K$) $\equiv$ $K$-module.
$K$-Vector Spaces $\hookrightarrow$ $K$-modules
For the categorically minded: a familiar example of a module is a vector space $V$ over a field $K$; this is a module over $K$ in the category of abelian groups: every element of $K$ acts on the vector space by a multiplication of vectors, and this action respects the addition of vectors.
Tensors play analogous conceptual roles.
- A tensor is a multidimensional array of numbers.
- A tensor is multiple weighted directions in space.
- A tensor is an element of a free monoid over the base ring. (If you don’t know what a free monoid is, don’t worry. I’ll go over them later in this post.)
An explanation of tensors as type constructors is postscript for fellow Haskell enthusiasts. Continue reading A Gentle Introduction to Tensors and Monoids