Vectors

Vectors, concretely, are arrows, with a head and a tail. If two arrows share a tail, then you can measure the angle between them. The length of the arrow represents the magnitude of the vector.

The modern abstract view is much more interesting but let’s start at the beginning.

Force vectors

Originally vectors were conceived as a force applied at a point.

As in, “That lawn ain’t mowing itself, boy. Now you git over there and apply a continuous stream of vectors to that lawnmower, before I apply a high-magnitude vector to your bee-hind!”

Thanks Galileo, totally gonna get you back, man

The Galilean idea of splitting a point into its x-coordinate, y-coordinate and z-coordinate works with vectors as well. “Apply a force that totals 5 foot-pounds / second² in the x direction and 2 foot-pounds / second² in the y direction”, for instance.

Therefore, both points and vectors benefit from adding more dimensions to Galileo’s “coordinate system”. Add a w dimension, a q dimension, a ξ dimension – and it’s up to you to determine what those things can mean.

If a vector can be described as (5, 2, 0), then why not make a vector that’s (5, 2, 0, 1.1, 2.2, 19, 0, 0, 0, 3)? And so on.

4th Dimension Plus

So that’s how you get to 4-D vectors, 13-D vectors, and 11,929-D vectors. But the really interesting stuff comes from considering ∞-dimensional vectors. That opens up functional space, and sooooo many things in life are functions.

(Interesting stuff also happens when you make vectors out of things that are not traditionally conceived to be “numbers”. Another post.)

Abstractions

In the most general sense, vectors are things that can be added together. The modern, abstract view includes as vectors:

lists
1-D arrays
bitstreams
linear functionals
force vectors
personal preferences
decisions
desires
the flow of heat
dinosaur tracks
tying a knot
economic transactions
a story or article, in any language
a poem
water flowing
time series
one instant during an argument
a curve
probabilities associated with various outcomes
marketing data
statistical observations
bids and asks
the quantum numbers of an atom
waveforms
signals
songs
heartbeats
one solution of a differential equation
a polynomial
a jpeg or bitmap of the Mona Lisa
a set of instructions
a dance move
someone’s signature
a secret message
a Taylor series
a Fourier decomposition
turning your mattress
(which you’re apparently supposed to do once a season)
intentions
electromagnetic flux
part of a trajectory
one wisp of the wind
states of affairs
logical propositions
distortions in a crystal lattice
a rotation of Rubik’s cube
neuronal spike-trains – so, thoughts? perceptions?
colour

Things you can do with vectors

Given two vectors, you should be able to take their outer product or their inner product.

The inner product allows you to measure the angle between two vectors. If the inner product makes sense, then the space you are playing in has geometry. (Not all spaces have geometry – some just have topology.)

And – this is weird – if the concept of angle applies, then the concept of length applies as well. Don’t ask me why; the symbols just work that way.

Magnitude

But the “length” of a song (one of my for-instances above) would not be something like 2:43. The magnitude of a song vector would be the total amount of energy in the sound wave | compression wave.

$\| \text{song} \| = \int \text{compression wave}$

What is the angle between two songs, two spike-trains, two security prices? What is the angle between two heartbeats? It’s the correlation between them.

Linear Algebra

Also, you can do linear algebra on vectors – provided they’re coming out of the same point. Some might say that the ability to do linear algebra on something is what makes a vector.

That can mean different things in different spaces – like maybe you’re superposing wave-forms, or maybe you’re converting bitmap images to JPEG. Or maybe you’re Photoshopping an existing JPEG. Oh, man, Photoshop is so math-y.