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Linear Algebra

  1. Vectors
    1. Scalars
    2. Vectors vs Sets
    3. Addition and Subtraction
    4. Scalar Multiplication
    5. Zero Vectors
    6. Linear Combinations
    7. Real Dot Product
    8. Length of a Vector
    9. Orthogonal Vectors
    10. Parallel Vectors
    11. Angle Between Vectors
    12. Unit Vectors
  2. Matrices
    1. Notation
    2. Indexing
    3. Submatrices
    4. Matrix-by-Vector Product
    5. Addition and Subtraction
    6. Scalar Multiplication
    7. Transpose
    8. Symmetries
    9. Matrix Multiplication
    10. Identity Matrix
    11. Non-Negative Integer Powers
    12. Reverse Order Law of Transposition
  3. Linear Systems
    1. Inverse Matrices
    2. Singular Matrices
    3. Linear Dependence
    4. Solutions
  4. Planes
    1. Vector Cross Product
  5. Gaussian Elimination
Linear Algebra β€ΊVectors β€ΊUnit Vectors

Unit Vectors

The concept of a unit vector is very simple, but very important and foundational in the field of Linear Algebra.

A unit vector is simply a vector whose length equals 111.

The use of a vector with length 111 is that you don’t care about the length - you only care about the direction it’s pointing to. The unit vector isolates the direction from its magnitude (length);

This could be useful because maybe you want to scale a vector to have some specific length. To do this you could first find the unit vector which points in the same direction as your given vector. Then you could multiply the unit vector with a scalar (scalar multiplication) corresponding to your desired length.

To find the unit vector u⃗\vec{u}u of a vector v⃗\vec{v}v, you just divide v⃗\vec{v}v by its length.

That is

uβƒ—=vβƒ—βˆ₯vβƒ—βˆ₯.\vec{u} = \dfrac{\vec{v}}{\lVert \vec{v} \rVert}.u=βˆ₯vβˆ₯v​.

If u⃗\vec{u}u is found as shown above, then

βˆ₯uβƒ—βˆ₯=1.\lVert \vec{u} \rVert = 1.βˆ₯uβˆ₯=1.

NOTE: You cannot find the unit vector which points in the same direction as a zero vector. For one, it would not make any sense, since the zero vector has no direction. But most importantly, the length of a zero vector is 000, and the formula above would require you to divide by 000 in that case, which is undefined.

NOTE: Division by a scalar is simply multiplying by the multiplicative inverse. What that means is that dividing by some scalar sss is the same as multiplying by 1s\frac{1}{s}s1​. It is basically scalar multiplication.

Example

For example, let us find the unit vector which points in the same direction as the vector

vβƒ—=[3333].\vec{v} = \begin{bmatrix} 3 \\ 3 \\ 3 \\ 3 \end{bmatrix}.v=​3333​​.

We divide by the length to find the unit vector u⃗\vec{u}u:

uβƒ—=vβƒ—βˆ₯vβƒ—βˆ₯=vβƒ—32+32+32+32=vβƒ—36=vβƒ—6=[36363636]=[12121212].\begin{align*} \vec{u} &= \dfrac{\vec{v}}{\lVert \vec{v} \rVert} \\[1em] &= \dfrac{\vec{v}}{\sqrt{3^2 + 3^2 + 3^2 + 3^2}} \\[1em] &= \dfrac{\vec{v}}{\sqrt{36}} \\[1em] &= \dfrac{\vec{v}}{6} \\[1em] &= \begin{bmatrix} \frac{3}{6} \\[0.5em] \frac{3}{6} \\[0.5em] \frac{3}{6} \\[0.5em] \frac{3}{6} \\[0.5em] \end{bmatrix} \\ &= \begin{bmatrix} \frac{1}{2} \\[0.5em] \frac{1}{2} \\[0.5em] \frac{1}{2} \\[0.5em] \frac{1}{2} \\[0.5em] \end{bmatrix}. \end{align*}u​=βˆ₯vβˆ₯v​=32+32+32+32​v​=36​v​=6v​=​63​63​63​63​​​=​21​21​21​21​​​.​

If you now compute βˆ₯uβƒ—βˆ₯\lVert \vec{u} \rVertβˆ₯uβˆ₯, you will find that it will equal 1:

βˆ₯uβƒ—βˆ₯=(12)2+(12)2+(12)2+(12)2=14+14+14+14=1=1\begin{align*} \lVert \vec{u} \rVert &= \sqrt{ \left(\dfrac{1}{2}\right)^2 + \left(\dfrac{1}{2}\right)^2 + \left(\dfrac{1}{2}\right)^2 + \left(\dfrac{1}{2}\right)^2 } \\[1em] &= \sqrt{ \dfrac{1}{4} + \dfrac{1}{4} + \dfrac{1}{4} + \dfrac{1}{4} } \\[1em] &= \sqrt{1} = 1 \end{align*}βˆ₯uβˆ₯​=(21​)2+(21​)2+(21​)2+(21​)2​=41​+41​+41​+41​​=1​=1​
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