Difference between revisions of "Vector"
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== Vector Operations == | == Vector Operations == | ||
===Dot (Scalar) Product=== | ===Dot (Scalar) Product=== | ||
− | Consider two vectors <math>\bold{u}=\langle u_1,u_2,\ldots,u_n\rangle</math> and <math>\bold{v}=\langle v_1, v_2,\ldots,v_n\rangle</math> in <math>\mathbb{R}^n</math>. The dot product is defined as <math>\bold{u}\cdot\bold{v}=|\bold{u} | + | Consider two vectors <math>\bold{u}=\langle u_1,u_2,\ldots,u_n\rangle</math> and <math>\bold{v}=\langle v_1, v_2,\ldots,v_n\rangle</math> in <math>\mathbb{R}^n</math>. The dot product is defined as <math>\bold{u}\cdot\bold{v}=|\bold{u}||\bold{v}|\cos\theta=u_1v_1+u_2v_2+\cdots+u_nv_n</math>, where <math>\theta</math> is the angle formed by the two vectors. This also yields the geometric interpretation of the dot product: from basic right triangle trigonometry, it follows that the dot product is equal to the length of the projection (i.e. the distance from the head of <math>\bold{u}</math> to <math>\bold{v}</math> to the origin) of <math>\bold{u}</math> onto <math>\bold{v}</math> times the length of <math>\bold{v}</math>. Note that the dot product is <math>0</math> if and only if the two vectors are perpendicular. |
===Cross (Vector) Product=== | ===Cross (Vector) Product=== |
Revision as of 20:07, 12 February 2009
The word vector has many different definitions, depending on who is defining it and in what context. Physicists will often refer to a vector as "a quantity with a direction and magnitude." For Euclidean geometers, a vector is essentially a directed line segment. In many situations, a vector is best considered as an n-tuple of numbers (often real or complex). Most generally, but also most abstractly, a vector is any object which is an element of a given vector space.
A vector is usually graphically represented as an arrow. Vectors can be uniquely described in many ways. The two most common is (for 2-dimensional vectors) by describing it with its length (or magnitude) and the angle it makes with some fixed line (usually the x-axis) or by describing it as an arrow beginning at the origin and ending at the pint . An
-dimensional vector can be described in this coordinate form as an ordered
-tuple of numbers within angle brackets or parentheses,
. The set of vectors over a field is called a vector space.
Contents
Description
Every vector has a starting point
and an endpoint
. Since the only thing that distinguishes one vector from another is its magnitude or length, and direction, vectors can be freely translated about a plane without changing. Hence, it is convenient to consider a vector as originating from the origin. This way, two vectors can be compared by only looking at their endpoints. This is why we only require
values for an
dimensional vector written in the form
. The magnitude of a vector, denoted
, is found simply by
using the distance formula.
Addition of Vectors
For vectors and
, with angle
formed by them,
.
|
Addition of vectors |
From this it is simple to derive that for a real number ,
is the vector
with magnitude multiplied by
. Negative
corresponds to opposite directions.
Properties of Vectors
Since a vector space is defined over a field , it is logically inherent that vectors have the same properties as those elements in a field.
For any vectors ,
,
, and real numbers
,
(Commutative in +)
(Associative in +)
- There exists the zero vector
such that
(Additive identity)
- For each
, there is a vector
such that
(Additive inverse)
(Unit scalar identity)
(Associative in scalar)
(Distributive on vectors)
(Distributive on scalars)
Vector Operations
Dot (Scalar) Product
Consider two vectors and
in
. The dot product is defined as
, where
is the angle formed by the two vectors. This also yields the geometric interpretation of the dot product: from basic right triangle trigonometry, it follows that the dot product is equal to the length of the projection (i.e. the distance from the head of
to
to the origin) of
onto
times the length of
. Note that the dot product is
if and only if the two vectors are perpendicular.
Cross (Vector) Product
The cross product between two vectors and
in
is defined as the vector whose length is equal to the area of the parallelogram spanned by
and
and whose direction is in accordance with the right-hand rule.
If and
, then the cross product of
and
is given by
![$\vec{a}\times\vec{b}=\begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3\end{vmatrix}.$](http://latex.artofproblemsolving.com/a/4/e/a4e3c957e1fe87a492051fb4ad1854b0075abd2a.png)
where are unit vectors along the co-ordinate axes.
Triple Scalar Product
The triple scalar product of three vectors is defined as
. Geometrically, the triple scalar product gives the signed area of the parallelpiped determined by
and
. It follows that
![$(\bold{a}\times\bold{b})\cdot \bold{c} = (\bold{c}\times\bold{a})\cdot \bold{b} = (\bold{b}\times\bold{c})\cdot \bold{a}.$](http://latex.artofproblemsolving.com/2/f/1/2f1162b7eb4c301897dba471b3f4372b0a70cec7.png)
It can also be shown that
![$(\bold{a}\times\bold{b})\cdot \bold{c} = \begin{vmatrix} a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3 \\ c_1 & c_2 & c_3 \end{vmatrix}.$](http://latex.artofproblemsolving.com/f/a/6/fa6e7cbf53bb81ffed2d33a8e63a2942274b9def.png)