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This is our 5th post in the Cheenta Probability Series. This article teaches how to mathematically find the length of an earphone wire by its picture.

Let's explore some truths.

- A Line is made up of Points.
- A Curve is made up of Lines.
- Earphones are as Messy.

This article is all about connecting these three truths to a topic in Probability Theory \( \cap \) Geometry, which is not so famous among peers, yet its' usefulness has led one to make an app in Google Play Store, which has only one download (by me). The sarcasm is towards the people, who didn't download. (obviously).

Today is the day for **Cauchy Crofton's Formula**, which can measure the length of any curve using random straight lines by counting points. It is all encoded in the formula.

\( L(c)= \frac{1}{2} \times \iint n(p, \theta) dp d \theta \)

This is the begining of a topic called **Integral Geometry.**

This formula intuitively speaks the truth

The Length of a Curve is the

ExpectedNumber of Times a "Random" Line Intersects it.

**I mean a "Random" Line.**

Thus the **Space of all Lines in \( \mathbf{R}^2 \)** can be represented in "**kinda**" polar coordinates **S** =** {\({(\theta, p) \mid 0 \leq \theta \leq 2 \pi, p \geq 0},\)**} where \(p, \theta\) are as indicated.

Now, we are now uniformly selecting this \( (\theta, p) \) over S. This is how we select a "**Random**" Line.

If C is the curve, whose length we are interested to measure. Then, \( L(C)= \frac{1}{2} \times \iint n(p, \theta) dp d \theta \).

\( L(C) \) = The Length of the curve

\( n(\theta, p) \) = The Number of times "Random Line" corresponding to \( (\theta, p) \) intersects C.

Crofton meant the following on a pretty, differentiable, and cute (regular) curve C that:

\( L(C)= \frac{1}{2} \times E_{(p, \theta)} [n(p, \theta)] \)

Here, we will find the length of a Line using "Random Lines". We will see, how counting points on the line, can help us find the length of a line.

Here, we choose C = Line.

A Line intersects another Line exactly once. \( n(p, \theta) = 1 \). Hence,

\( L(C)= \frac{1}{2} \times \iint n(p, \theta) dp d \theta = \frac{1}{2} \times \iint dp d\theta = \frac{1}{2} \times \int_{0}^{2 \pi}\left(\int_{0}^{|\cos \theta|(1 / 2)} d p\right) d \theta = \frac{1}{2} \times \int_{0}^{2 \pi} l / 2|\cos \theta| d \theta= l \)

**Approximate Curves by Lines. **

Refer to **Approximation of Curves by Line Segments by Henry Stone**.

Now, take apply the result on these lines. By linearity of expectation and the uniform convergence of the Lines to the Curve, we get the same for the curve.

Suppose that the curve *c* is parameterized on the interval [a,b]. Define a partition \( P \) to be a collection of points that subdivides the interval, say { \( a = a_0, a_1, a_2, ..., a_n = b\) }.

Define \( L_{r}(c)=\sum_{i=1}^{n} |c\left({a}_{i-1}\right)-c\left({a}_{i}\right)| \)

Then \( L(c)= sup_{r} L{r}(c) \)

Now, each of the \( |c\left({a}_{i-1}\right)-c\left({a}_{i}\right)|\) are approximated by the Crofton's Formula. Now, taking the limit gives ust eh required result. QED.

Create a Mesh of Lines (Coordinate System) - A Fixed Sample representing the Population of the Random Lines. Then count the number of intersections using those mesh of lines only and add it up.

The mathematics of the above argument is as follows.

- Construct a grid of lines parallel to the x-axis at a distance
*r*apart. - Rotate this family of curves about the origin by \( \frac{\pi}{3}, \frac{2\pi}{3} \) to get a system of 3 parallel system of lines. (We can make this finer).
- Now if a line in the grid intersects a curve n times, there might be more intersections if we consider all lines in \( \mathbf{R}^{2} \)- we only know about the grid lines. The parameters of these unknown lines can range from 0 to \(r\) and from 0 to \( \frac{\pi}{3} \)
- Therefore we can approximate the length of C by:

\( L(c)= \frac{1}{2} \times \iint n(p, \theta) dp d \theta \cong \frac{1}{2} \times n r \times \frac{\pi}{3} \)

An example is show below. This is done in the app named **Cauchy-Crofton App**, which unfortunately is not working now and I have reported.

There are lots of corollaries coming up like Isoperimetric Inequality, Barbier's Result, etc. I will discuss these soon. Till then,

Stay Tuned!

Stay Blessed!

- Coincidence Statistics - Cheenta Probability Series
- Understanding Statistical Regularity - Cheenta Probability Series
- Repeated Rolle's Theorem - Video

What to do to shape your Career in Mathematics after 12th?

From the video below, let's learn from Dr. Ashani Dasgupta (a Ph.D. in Mathematics from the University of Milwaukee-Wisconsin and Founder-Faculty of Cheenta) how you can shape your career in Mathematics and pursue it after 12th in India and Abroad. These are some of the key questions that we are discussing here:

- What are some of the best colleges for Mathematics that you can aim to apply for after high school?
- How can you strategically opt for less known colleges and prepare yourself for the best universities in India or Abroad for your Masters or Ph.D. Programs?
- What are the best universities for MS, MMath, and Ph.D. Programs in India?
- What topics in Mathematics are really needed to crack some great Masters or Ph.D. level entrances?
- How can you pursue a Ph.D. in Mathematics outside India?
- What are the 5 ways Cheenta can help you to pursue Higher Mathematics in India and abroad?

Cheenta has taken an initiative of helping College and High School Passout Students with its "Open Seminars" and "Open for all Math Camps". These events are extremely useful for students who are really passionate for Mathematic and want to pursue their career in it.

Cheenta is a knowledge partner of Aditya Birla Education Academy

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