The mathematical beauty of epicycles

Juan Carlos Ponce Campuzano

πŸ”— jcponce.com

The mathematical beauty of epicycles

A mysterious curve

What are epicycles?

πŸ€”

A circle moving on another circle.

What are epicycles?

πŸ˜ƒ

A circle moving on another circle, on another circle.

What are epicycles?

πŸ˜ƒ

A circle moving on another circle, on another circle, on another circle...

What are epicycles?

\left\{ \begin{array}{l} x(t) \\ y(t) \end{array} \right. 0\leq t \leq 2\pi
\big(x(t) , y(t) \big)

πŸ€”

How can we represent them mathematically?

A parametric function!

\big(x , y \big)

What are epicycles?

πŸ€”πŸ”

RAWK QT8A

Code:

What are epicycles?

πŸ€”πŸ”

Work only withΒ 

  • Simple rotation
  • Double rotation

RAWK QT8A

Code:

\left\{ \begin{array}{l} R \cos( \omega t) \\ R\, \sin(\omega t) \end{array} \right. 0\leq t \leq 2\pi

Simple rotations

Simple rotations

\(\sin x\)

Simple rotations

\(\sin x\) and \(\cos x\)

Double rotations

\left\{ \begin{array}{l} R_1 \cos(\omega_1 t) + R_2 \cos(\omega_2 t)\\ R_1 \,\sin(\omega_1 t) + R_2 \,\sin(\omega_2 t) \end{array} \right.

Triple rotations

\left\{ \begin{array}{l} R_1 \cos(\omega_1 t) + R_2 \cos(\omega_2 t) + R_3 \cos(\omega_3 t) \\ R_1 \sin(\omega_1 t) + R_2 \sin(\omega_2 t) + R_3 \sin(\omega_3 t) \end{array} \right.

Triple rotations

\left\{ \begin{array}{l} R_1 \cos(\omega_1 t) + R_2 \cos(\omega_2 t) + R_3 \cos(\omega_3 t) \\ R_1 \,\sin(\omega_1 t) + R_2 \,\sin(\omega_2 t) + R_3 \sin(\omega_3 t) \end{array} \right.
R_1 = 1, R_2 = \dfrac{1}{2}, R_3 = \dfrac{1}{3}
\omega_1 = 1,
\omega_2 =6,
\omega_3 = -14

πŸ‘‰

Complete last task!

\left\{ \begin{array}{l} \displaystyle R_1\cos(\omega_1 t + \phi_1) + \cdots +R_N\cos(\omega_N t + \phi_N) \\ \displaystyle R_1\sin(\omega_1 t + \phi_1) + \cdots +R_N\sin(\omega_N t + \phi_N) \end{array} \right.

In general we have:

0\leq t\leq 2\pi

What are epicycles?

What are epicycles?

\left\{ \begin{array}{l} \displaystyle \sum_{k=1}^{N} R_k\cos(\omega_k t + \phi_k) \\ \displaystyle \sum_{k=1}^{N}R_k\sin(\omega_k t + \phi_k) \end{array} \right. \; 0\leq t\leq 2\pi

In general we have:

This new symbol \(\phi_k\) indicates how much the disk \(k\) is initially rotated at time \(t = 0\), and we called a phase offset.

If we do not specify a phase offset, we can only describe epicycles where the circles start aligned.

What are epicycles?

\left\{ \begin{array}{l} \displaystyle \sum_{k=1}^{N} R_k\cos(\omega_k t + \phi_k) \\ \displaystyle \sum_{k=1}^{N}R_k\sin(\omega_k t + \phi_k) \end{array} \right. \; 0\leq t\leq 2\pi

This new symbol \(\phi_k\) indicates how much the disk \(k\) is initially rotated at time \(t = 0\), and we called a phase offset.

If we do not specify a phase offset, we can only describe epicycles where the circles start aligned.

Question

It seems that the geometric shapes described

by epicycles are smooth closed curves.

But, do all epicycles have to be curvy or closed?Β 

πŸ€”

Line segment

\left\{ \begin{array}{l} R \cos(\omega t) + R \cos(-\omega t)\\ R \sin(\omega t ) + R \sin(-\omega t ) \end{array} \right.
\begin{array}{l} = 2R \cos(\omega t) \\ = 0 \end{array}

Q \(=(2R\cos(\omega t),0)\)

\left\{ \begin{array}{l} R \cos(\omega t) + R \cos(\omega t)\\ R \sin(\omega t ) - R \sin(\omega t ) \end{array} \right.

πŸ€”

How can we determine the epicycles for our mysterious curve?

How can we determine the epicycles for our mysterious curve?

Before answering this question,

let's explore an interesting mathematical property.

Rotational symmetry exploration

Rotational symmetry exploration

\left\{ \begin{array}{l} R_1 \cos(\omega_1 t) + R_2 \cos(\omega_2 t) + R_3 \cos(\omega_3 t) \\ R_1 \,\sin(\omega_1 t) + R_2 \,\sin(\omega_2 t) + R_3 \sin(\omega_3 t) \end{array} \right.
R_1 = 1, R_2 = \dfrac{1}{2}, R_3 = \dfrac{1}{3}
\omega_1 = 1, \omega_2 =6, \omega_3 = -14

{1, 6, -14}

Rotational symmetry exploration

Rotational symmetry exploration

{1, 6, -14}

Rotational symmetry exploration

What is the relationship between the frequencies \(\{1, 6, -14\}\) and the rotational symmetry of orderΒ \(5\)?

πŸ€”

Rotational symmetry exploration

What is the relationship between the frequencies \(\{1, 6, -14\}\) and the rotational symmetry of orderΒ \(5\)?

πŸ€”

ZT7S CNXU

Code:

Rotational symmetry exploration

\(1-6=-5\)

\(6-(-14)=20\)

\(-14-1=-15\)

The greatest common divisor (GCD) of \(-5, 20,\) and \(-15\) is:

5

Rotational symmetry exploration

What is the order of symmetry for the values

-2, 5, 19?

Rotational symmetry exploration

What is the order of symmetry for the values

2, 8, -10?

Note that 2, 8, and -10 have a common factor.

How can we determine the epicycles for our mysterious curve?

c(t) = \left\{ \begin{array}{l} R_1 \cos(\omega_1 t) + R_2 \cos(\omega_2 t) + R_3 \cos(\omega_3 t) \\ R_1 \sin(\omega_1 t) + R_2 \sin(\omega_2 t) + R_3 \sin(\omega_3 t) \end{array} \right.
(0\lt R_k\in \mathbb R, \;\omega_k\in \mathbb Z)

\(R_1, R_2, R_3\) are positive real numbers and \(\omega_1, \omega_2, \omega_3\) are also real numbers.

How can we determine the epicycles for our mysterious curve?

It is going to get complex! πŸ™ƒ

(\cos t, \sin t)
=\cos t + i \sin t
= e^{i t}
\big(R_1 \cos (\omega_1 t), R_1 \sin (\omega_1 t)\big)
= R_1e^{i \omega_1 t}
i = \sqrt{-1}
c(t) = \left\{ \begin{array}{l} R_1 \cos(\omega_1 t) + R_2 \cos(\omega_2 t) + R_3 \cos(\omega_3 t) \\ R_1 \sin(\omega_1 t) + R_2 \sin(\omega_2 t) + R_3 \sin(\omega_3 t) \end{array} \right.
0\lt R_k\in \mathbb R, \;\omega_k\in \mathbb Z

It is going to get complex! πŸ™ƒ

c(t)= R_1e^{ \omega_1 i t}+R_2e^{ \omega_2 i t}+R_3e^{ \omega_3 i t}
0\lt R_k\in \mathbb R, \;\omega_k\in \mathbb Z

It is going to get complex! πŸ™ƒ

c(t)= C_1e^{ \omega_1 i t}+C_2e^{ \omega_2 i t}+C_3e^{ \omega_3 i t}
C_k \text{ is a complex number}, \;\omega_k\in \mathbb Z

It is going to get complex! πŸ™ƒ

C_k = a + i b = (a,b)

The mysterious curve

c(t) = e^{it} + \dfrac{1}{2}e^{6 i t} + \dfrac{i}{3}e^{-14 i t}
c(t)= C_1e^{ \omega_1 i t}+C_2e^{ \omega_2 i t}+C_3e^{ \omega_3 i t}
C_1=1,\,C_2=\dfrac{1}{2},\, C_3= \dfrac{i}{3}
\omega_1=1,\,\omega_2=6,\, \omega_3=-14

The mysterious curve

c(t) = \left\{ \begin{array}{l} \displaystyle \cos( t) +\frac{1}{2}\cos(6 t) +\frac{1}{3}\sin(14 t) \\ \\ \displaystyle \sin( t) +\frac{1}{2} \sin(6 t)\, +\frac{1}{3} \cos(14 t) \end{array} \right.

Using properties of complex numbers:

\(i\cdot i = -1\)

More mystery curves

c(t)= C_1e^{ \omega_1 i t}+C_2e^{ \omega_2 i t}+C_3e^{ \omega_3 i t}
c(t)= C_1e^{ \omega_1 i t}+C_2e^{ \omega_2 i t}+\cdots + C_Ne^{ \omega_N i t}

More mystery curves

c(t)= C_1e^{ \omega_1 i t}+C_2e^{ \omega_2 i t}+\cdots + C_Ne^{ \omega_N i t}

In fact we can use this equation to create more complex epicycles!

c(t)= C_1e^{ \omega_1 i t}+C_2e^{ \omega_2 i t}+\cdots + C_Ne^{ \omega_N i t}

🀯

c(t)= \displaystyle \sum_{k=1}^{N} C_ke^{ \omega_k i t }

Discrete Fourier Transform

x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

In fact we can use this equation to create more complex epicycles!

πŸ€”

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

\(\Bigg\{\Bigg.\)

Discrete Fourier Transform (DFT)

πŸ‘ˆ DFT

The inverse of the DFT

πŸ‘ˆ

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }
c(t)= C_1e^{ \omega_1 i t}+C_2e^{ \omega_2 i t}+\cdots + C_Ne^{ \omega_N i t}

They are very similar to this:

\(\Bigg\{\Bigg.\)

Discrete Fourier Transform (DFT)

πŸ€”

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

They are very similar to this:

\(\Bigg\{\Bigg.\)

Discrete Fourier Transform (DFT)

c(t) = \left\{ \begin{array}{l} \text{Sum of a bunch sines and cosines} \\ \text{Sum of a bunch sines and cosines} \end{array} \right.

πŸ˜ƒ

Discrete Fourier Transform (DFT)

A nice methaphor πŸ˜ƒ

  • What does the Discrete Fourier Transform do?

Given a smoothie, it finds the recipe.

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }

A nice methaphor 🧐

  • What does the Discrete Fourier Transform do?

Given a smoothie, it finds the recipe.

  • How?

Run the smoothie through filters to extract each ingredient.

  • Why?

Recipes are easier to analyze, compare, and modify than the smoothie itself.

  • How do we get the smoothie back?

Blend the ingredients.

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

Applications of the DFT

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

Modern digital media

Applications of the DFT

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

Video

Applications of the DFT

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

Images

Applications of the DFT

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

Sound

Applications of the DFT

X_k = \displaystyle \frac{1}{N} \sum_{n=0}^{N-1} x_n \cdot e^{- i k \frac{2 \pi }{N} n }
x_n =\displaystyle \sum_{ k=0}^{N-1} X_{k} \cdot e^{ i k \frac{2 \pi }{N} n }

Magnetic Resonance Imaging

Thanks!

dynamicmath.xyzΒ