Vector
A vector is alternate notation for an n tuple, so that is the n-tuple
Collinear
Given a vector space , we say that two vectors are collinear if there exists an such that
The length of a Vector
Given a vector , we define its length by
Angle Between Nonzero Vectors
Given nonzero vectors , the angle between and is the smaller Euclidean angle between the rays from the origin in the directions and . It is the unique value representing that smaller angle.
Linearly Independent Nonzero Vectors Have Non-Extreme Angle
Suppose are linearly independent, and let be the angle between them. Then
If , then and point along the same ray, so one is a positive scalar multiple of the other. If , then and point along opposite rays, so one is a negative scalar multiple of the other. In either case, and are collinear, so is linearly dependent. This contradicts the assumption that are linearly independent.
Dot Product Algebraic Definition
Given two vectors and in , their dot product is the real number
Thus .
Dot Product is Symmetric
For any ,
Write and . By the algebraic definition of the dot product and commutativity of multiplication in ,
Dot Product Distributes into Vector Addition from the Right
For any ,
Write , , and . By the definition of the dot product,
Dot Product Distributes into Vector Addition from the Left
For any ,
Dot Product is Compatible with Scalar Multiplication
For any and ,
By the definition of the dot product,
The second equality follows from this equality and the symmetry of the dot product:
Dot Product is Positive Definite
For any ,
Moreover if and only if .
By the definition of the dot product,
Since every square is non-negative, . Also, exactly when each , which happens exactly when each , i.e. exactly when .
Norm Squared is the Dot Product
For any we have that
By the definition of length and the definition of the dot product,
Nonzero Vector has Positive Length
If and , then
By norm squared is the dot product and the fact that the dot product is positive definite, . Since is non-negative by the definition of length, it follows that .
Dot Product Expansion of Norm Squared
For any ,
and
Using norm squared is the dot product, dot product distributes into vector addition from the right, dot product distributes into vector addition from the left, and symmetry of the dot product, we get
Replacing by , and using compatibility with scalar multiplication, gives
Euclidean Law of Cosines
Suppose a triangle has side lengths , , and , and suppose that is the angle between the sides of length and . Then
TODO: Add a Euclidean geometry proof here.
Dot Product Geometric Formula
If are non-zero and is the angle between and , then
The vectors , , and determine a triangle with side lengths , , and . By the Euclidean law of cosines applied to this triangle,
On the other hand, by the dot product expansion of norm squared,
Equating the two expressions and subtracting from both sides gives
Dividing by , we get
Vector Form of a Line
Suppose that are vectors, then we say that the set is a line and say that the vector equation for the line is
We also say that is the direction vector for
Norm Equals Absolute Dot Product with a Parallel Unit Vector
Let be a unit vector. If for some , then
Since and is a unit vector,
Also,
because . Therefore .
Dot Product of a Vector Parallel to a Unit Vector
Let , and suppose is a unit vector. If for some , then
Since ,
Since is a unit vector,
Therefore .
Positively Oriented Triple in R3
An ordered triple of nonzero vectors in is positively oriented if it has the same orientation as the standard coordinate directions . Equivalently, when the fingers of the right hand curl from the direction of toward the direction of , the thumb points in the direction of .
Cross Product
Given two nonzero vectors , we define their cross-product to be
where is the angle between and , and is a unit vector such that is positively oriented.
Cross Product Vector Component Formula
An easy way to remember this is ab 231 where you then get a2b3 - ..., a3b1 - ..., a1b2
Cross Product is Orthogonal to its Factors
If , then
Write and . By the definition of the dot product and the component formula for the cross product,
The same calculation gives
Cross Product Distributes Over Vector Addition in the Second Input
If , then
Write the vectors in coordinates. The component formula for the cross product shows that each component of distributes over the coordinate sums in . Therefore .
Cross Product Scalar Multiplication in the Second Input
If and , then
Write the vectors in coordinates. The component formula for the cross product shows that each component of has a common factor . Factoring it out gives .
Cross Product is Anti-Commutative
If , then
Write and . By the component formula for the cross product,
Multiplying by gives
Cross Product Distributes Over Vector Addition in the First Input
If , then
By anti-commutativity, distribution in the second input, and anti-commutativity again,
Cross Product Scalar Multiplication in the First Input
If and , then
By anti-commutativity, scalar multiplication in the second input, and anti-commutativity again,
Cross Product Expands Over Two Vector Sums
If , then
By distribution in the second input,
By distribution in the first input,
Reordering the sum gives
Oriented Projected Area Identity
Let be a unit vector. For , define
Then
By expanding the cross product over vector addition and pulling scalar factors out of the first and second inputs,
Since , the last term is . Also and are orthogonal to their factors, so both are orthogonal to . Taking the dot product with leaves
Plane Through the Origin as a Span
Suppose are linearly independent. The plane through the origin generated by and is the span
Plane Through the Origin by a Normal
Suppose and . The plane through the origin with normal vector is defined using the dot product by
Span Plane has Cross Product Normal
Suppose are linearly independent. Then
Let .
Let be the angle between and . Since , we have and by nonzero vectors have positive length. Since and are linearly independent, the angle satisfies and by linearly independent nonzero vectors have non-extreme angle. Also by the definition of angle, so by sine is zero on only at the endpoints. Therefore, by the definition of the cross product,
and so .
First suppose that . By the definition of span, for some . Since is orthogonal to both and by the cross product is orthogonal to its factors proposition,
Thus For the reverse containment, note that are linearly independent. To see this, suppose that Taking the dot product of both sides with , we get Since , , and by norm squared is the dot product, it follows that . Therefore , and since are linearly independent, we get . Thus are linearly independent.Since by the dimension of , the three linearly independent vectors form a basis of .
Now suppose that . Since form a basis, we can write . Then
Since , we have . Thus , so by the definition of span.
Translated Plane as a Span
Suppose , suppose , and suppose that and are linearly independent. The plane through with direction vectors and is the translation of the plane through the origin as a span:
Translated Plane by a Normal
Suppose and . The plane through with normal vector is defined by translating the plane through the origin by a normal:
By the dot product, this can equivalently be written as .
Coordinate Equation of a Plane
Suppose , and suppose that . The equation
defines the plane
whose normal vector is , as shown by its equivalence with the translated plane by a normal.
Coordinate Equation of a Plane is Normal Form
Suppose , , and . Then
Let . By the definition of the dot product, we have
Therefore the coordinate equation is exactly the translated normal form written out component by component.
Translated Span Plane Equals Translated Normal Plane
Suppose , suppose , and suppose that and are linearly independent. Then
Let . By the translated plane as a span definition, exactly when . By the span plane has cross product normal proposition, this happens exactly when , which is exactly the normal equation
Equation for a Line
We say the equation of a line is given by where where the line is given by the set
Equation of a Line as a 3d Dot Product
Suppose that is given by then we have
TODO: Add the proof here.
Equation of a Line Given by the Cross Product
Suppose that and consider then the equation of the line that passes through is given by
We know that defines a line, but we need to verify that are both on that line, but since and we know that they are on the line, as needed.
The Norm of The Half of The Sum of Two Unit Vectors is One iff They are Equal
Suppose such that then
Suppose that we'd like to prove that , thus it's equivalent to show that , recall that from the parallelogram law that thus it's enough to show that , which means we just have to show that , moreover were unit vectors so we have and we now just need to prove that . We've assumed that , this means that thus we conclude that as needed.
Suppose that , then as needed.
Vector Cosine Law
Suppose that and is the angle between them, then
Dot Product Is a Sum of Norms
Rearrange the first equality in the dot product expansion of norm squared.