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What is the rigorous definition of "Vector" (& " Scalar")? Best I got was:

https://www.youtube.com/watch?v=Ncx98PmXbZc

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    $\begingroup$ 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 $\endgroup$ Commented 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 Bot
    Commented 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. $\endgroup$ Commented 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 1

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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

  1. Associativity: i.e. $(a+b)+c=a+(b+c)$

  2. Commutativty: i.e $a+b=b+a$

  3. 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 $0$)

  4. 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.

  1. Associativity $(a \cdot b) \cdot c = a \cdot (b \cdot c)$

  2. Commutivity $a \cdot b= b \cdot a$

  3. Existence of neutral element (denoted by $1$)

  4. 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

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