What is the rigorous definition of "Vector" (& " Scalar")? Best I got was:
-
2$\begingroup$ Eigenchris is a nice youtube channel from which I could recommend the playlist 'tensors for beginners'. Vectors and scalars (in physics and maths) are defined by how they transform under a transformation $\endgroup$– AccidentalTaylorExpansionCommented Jun 30, 2022 at 17:00
-
$\begingroup$ Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. $\endgroup$– Community BotCommented Jun 30, 2022 at 17:31
-
$\begingroup$ Can't beat this book, amazon.com/dp/3319307657 if you want to understand vectors from a mathematician's viewpoint. Very abstract, very formal, but surprisingly easy to read. $\endgroup$– Solomon SlowCommented Jun 30, 2022 at 19:13
-
$\begingroup$ Related: physics.stackexchange.com/q/155878/2451 $\endgroup$– Qmechanic ♦Commented Jun 30, 2022 at 19:33
1 Answer
The short answer is:
A vector is an element of a vector space, whereas a scalar is an element of the underlying field
In order to learn more about vector spaces you can use any introductory linear algebra book.
Long answer:
Definition Field:
Let $F$ be a set endowed with an interior operation.
$+: F \times F \longrightarrow F, (a, b) \mapsto a+b$
(This operation can be anything. You put in 2 elements of the set and get 1 back).
This operation should fullfill
Associativity: i.e. $(a+b)+c=a+(b+c)$
Commutativty: i.e $a+b=b+a$
There should be a neutral element, i.e. $\exists e \in K: a+e= a \ \ \forall \ \ a \in K $
(The neutral element is usually denoted by $0$)
For each element ther should be an inverse, i.e. $\forall a \in K \exists b \in K \ \ s.t. a+b = 0$
(The inverse is usually denoted by -a)
This first opertion is called an addition
Furthermore, there is second operation:
$\cdot : F \times F \longrightarrow F: (a, b) \mapsto a\cdot b$
With respect to which $F/0$ (Taking the neutral away) fullfills properties 1-4, i.e.
Associativity $(a \cdot b) \cdot c = a \cdot (b \cdot c)$
Commutivity $a \cdot b= b \cdot a$
Existence of neutral element (denoted by $1$)
Existence of inverse for all elements except $0$
Furthermore, there is distributivity between the operations, i.e.
$(a+b)\cdot c = a \cdot c + b \cdot c$
We call the triple $(F, +, \cdot)$ a field
Examples of fields include $\mathbb{R}, \mathbb{C}$
Definition Vector space:
A vector space $V$ over a field $F$ is a set, endowed with an addition
$+ : V \times V \longrightarrow V$
with the same property as the addition in the field
and a scalar mulitplication:
$\cdot: F \times V \longrightarrow V, (a, v) \mapsto a \cdot v,$
with: $1 \cdot v = v, \forall v \in V$
and distributivty, i.e for $a, b \in F,$ $v, w \in V$
$(a + b) \cdot v = a \cdot v + b \cdot v$
$a \cdot (v+w)= a \cdot v+b \cdot w$
Furthermore it respects the associativity of the field multiplication, i.e.
$(a\cdot b) \cdot v = a \cdot (b \cdot v)$ for $a, b \in F,$ $v \in V$
The elements of the field are called scalars the elements of the vector space are called vectors.
This is the formal definition