# Vectors/Vector Algebra

## Vector Algebra OperationsEdit

### Addition and SubtractionEdit

If and are vectors, then the sum is also a vector.

The two vectors can also be subtracted from one another to give another vector .

### Multiplication by a scalarEdit

Multiplication of a vector by a scalar has the effect of stretching or shrinking the vector.

You can form a unit vector that is parallel to by dividing by the length of the vector . Thus,

### Scalar product of two vectorsEdit

The *scalar* product or *inner* product or *dot* product of two vectors is defined as

where is the angle between the two vectors (see Figure 2(b)).

If and are perpendicular to each other, and . Therefore, .

The dot product therefore has the geometric interpretation as the length of the projection of onto the unit vector when the two vectors are placed so that they start from the same point (tail-to-tail).

The scalar product leads to a scalar quantity and can also be written in component form (with respect to a given basis) as

If the vector is dimensional, the dot product is written as

Using the Einstein summation convention, we can also write the scalar product as

Also notice that the following also hold for the scalar product

- (commutative law).
- (distributive law).

### Vector product of two vectorsEdit

The *vector* product (or *cross* product) of two vectors and is another vector defined as

where is the angle between and , and is a unit vector perpendicular to the plane containing and in the right-handed sense.

In terms of the orthonormal basis , the cross product can be written in the form of a determinant

In index notation, the cross product can be written as

where is the Levi-Civita symbol (also called the permutation symbol, alternating tensor).

## Identities from Vector AlgebraEdit

Some useful vector identities are given below.

- .
- .

For more details on the topics of this chapter, see Vectors in the wikibook on Calculus.